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Most Influential CIKM Papers (2024-09)

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The ACM Conference on Information and Knowledge Management (CIKM) is an annual computer science research conference dedicated to information management and knowledge management. Paper Digest Team analyzes all papers published on CIKM in the past years, and presents the 15 most influential papers for each year. This ranking list is automatically constructed based upon citations from both research papers and granted patents, and will be frequently updated to reflect the most recent changes. To find the latest version of this list or the most influential papers from other conferences/journals, please visit Best Paper Digest page. Note: the most influential papers may or may not include the papers that won the best paper awards. (Version: 2024-09)

To search or review papers within CIKM related to a specific topic, please use the search by venue (CIKM) and review by venue (CIKM) services. To browse the most productive CIKM authors by year ranked by #papers accepted, here are the most productive CIKM authors grouped by year.

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TABLE 1: Most Influential CIKM Papers (2024-09)

Year Rank Paper Author(s)
2023 1 Large Language Models As Zero-Shot Conversational Recommenders
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Highlight: In this paper, we present empirical studies on conversational recommendation tasks using representative large language models in a zero-shot setting with three primary contributions. (1) Data: To gain insights into model behavior in in-the-wild conversational recommendation scenarios, we construct a new dataset of recommendation-related conversations by scraping a popular discussion website.		 ZHANKUI HE et. al.
2023 2 Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting
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Highlight: In this study, we present a novel component called spatio-temporal adaptive embedding that can yield outstanding results with vanilla transformers.		 HANGCHEN LIU et. al.
2023 3 XuanYuan 2.0: A Large Chinese Financial Chat Model with Hundreds of Billions Parameters
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Highlight: However, there is a scarcity of open-sourced chat models specifically designed for the Chinese language, especially in the field of Chinese finance, at the scale of hundreds of billions. To address this gap, we introduce XuanYuan 2.0, the largest Chinese chat model to date, built upon the BLOOM-176B architecture.		 Xuanyu Zhang; Qing Yang;
2023 4 Prompt Distillation for Efficient LLM-based Recommendation
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Highlight: To address the problems, we propose to distill the discrete prompt for a specific task to a set of continuous prompt vectors so as to bridge IDs and words and to reduce the inference time.		 Lei Li; Yongfeng Zhang; Li Chen;
2023 5 DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction
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Highlight: Although transformer-based models have made progress in this field, they usually do not make full use of three features of multivariate time series: global information, local information, and variables correlation. To effectively mine the above three features and establish a high-precision prediction model, we propose a double sampling transformer (DSformer), which consists of the double sampling (DS) block and the temporal variable attention (TVA) block.		 CHENGQING YU et. al.
2023 6 Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Models
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Highlight: In this paper, we propose a robust discriminator named RelD to effectively detect hallucination in LLMs’ generated answers.		 YUYAN CHEN et. al.
2023 7 Continual Learning for Generative Retrieval Over Dynamic Corpora
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Highlight: The ability to incrementally index new documents while preserving the ability to answer queries with both previously and newly indexed relevant documents is vital to applying GR models. In this paper, we address this practical continual learning problem for GR.		 JIANGUI CHEN et. al.
2023 8 Unlocking The Potential of User Feedback: Leveraging Large Language Model As User Simulators to Enhance Dialogue System
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Highlight: Motivated by the goal of leveraging LLMs, we propose an alternative approach called User-Guided Response Optimization (UGRO) to combine it with a smaller TOD model.		 Zhiyuan Hu; Yue Feng; Anh Tuan Luu; Bryan Hooi; Aldo Lipani;
2023 9 On The Trade-off Between Over-smoothing and Over-squashing in Deep Graph Neural Networks
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Highlight: To achieve a suitable compromise, we propose adding and removing edges as a viable approach.		 Jhony H. Giraldo; Konstantinos Skianis; Thierry Bouwmans; Fragkiskos D. Malliaros;
2023 10 Toward A Foundation Model for Time Series Data
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Highlight: In this paper, we aim to develop an effective time series foundation model by leveraging unlabeled samples from multiple domains.		 CHIN-CHIA MICHAEL YEH et. al.
2023 11 An Unified Search and Recommendation Foundation Model for Cold-Start Scenario
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Highlight: We propose a novel framework called S&R Multi-Domain Foundation, which uses LLM to extract domain invariant features, and Aspect Gating Fusion to merge the ID feature, domain invariant text features and task-specific heterogeneous sparse features to obtain the representations of query and item.		 YUQI GONG et. al.
2023 12 Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems
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Highlight: The optimal stage (early or late) to fuse modality features into item representations is still debated. We propose a graph-based approach (named MMSR) to fuse modality features in an adaptive order, enabling each modality to prioritize either its inherent sequential nature or its interplay with other modalities.		 Hengchang Hu; Wei Guo; Yong Liu; Min-Yen Kan;
2023 13 AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation
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Highlight: Given that softmax-based attention may promote unimodal activation, we propose the Squeeze-Excitation Attention (with sigmoid activation) into SR models to capture multiple pertinent items (keys) simultaneously.		 JUYONG JIANG et. al.
2023 14 NOVO: Learnable and Interpretable Document Identifiers for Model-Based IR
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Highlight: However, these docids are not specifically optimized for retrieval tasks, which makes it difficult to learn semantics and relationships between documents and achieve satisfactory retrieval performance. To address the above limitations, we propose Neural Optimized VOcabularial (NOVO) docids.		 Zihan Wang; Yujia Zhou; Yiteng Tu; Zhicheng Dou;
2023 15 Uncertainty Quantification Via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction
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Highlight: This dilemma arises from the numerous zeros and over-dispersed demand patterns within these matrices, which challenge the Gaussian assumption inherent to deterministic deep learning models. To address these challenges, we propose a novel approach: the Spatial-Temporal Tweedie Graph Neural Network (STTD).		 XINKE JIANG et. al.
2022 1 Spatial-Temporal Identity: A Simple Yet Effective Baseline for Multivariate Time Series Forecasting
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Highlight: In this paper, we identify the indistinguishability of samples in both spatial and temporal dimensions as a key bottleneck, and propose a simple yet effective baseline for MTS forecasting by attaching <u>S</u>patial and <u>T</u>emporal <u>ID</u>entity information (STID), which achieves the best performance and efficiency simultaneously based on simple Multi-Layer Perceptrons (MLPs).		 Zezhi Shao; Zhao Zhang; Fei Wang; Wei Wei; Yongjun Xu;
2022 2 KuaiRec: A Fully-observed Dataset and Insights for Evaluating Recommender Systems
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Highlight: To the best of our knowledge, this is the first real-world fully-observed data with millions of user-item interactions. With this unique dataset, we conduct a preliminary analysis of how the two factors – data density and exposure bias – affect the evaluation results of multi-round conversational recommendation.		 CHONGMING GAO et. al.
2022 3 RecBole 2.0: Towards A More Up-to-Date Recommendation Library
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Highlight: In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics and architectures.		 WAYNE XIN ZHAO et. al.
2022 4 On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs
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Highlight: However, it is not well understood how GNNs work without natural node features, especially regarding the various ways to construct artificial ones. In this paper, we point out the two types of artificial node features, i.e., positional and structural node features, and provide insights on why each of them is more appropriate for certain tasks, i.e., positional node classification, structural node classification, and graph classification.		 Hejie Cui; Zijie Lu; Pan Li; Carl Yang;
2022 5 KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos
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Highlight: In this work, we present KuaiRand, an unbiased sequential recommendation dataset containing millions of intervened interactions on randomly exposed videos, collected from the video-sharing mobile App, Kuaishou.		 CHONGMING GAO et. al.
2022 6 PLAID: An Efficient Engine for Late Interaction Retrieval
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Highlight: To dramatically speed up the search latency of late interaction, we introduce the Performance-optimized Late Interaction Driver (PLAID) engine.		 Keshav Santhanam; Omar Khattab; Christopher Potts; Matei Zaharia;
2022 7 Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning
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Highlight: Inspired by the recent success of contrastive learning in mining supervised signals from data itself, in this paper, we focus on exploring contrastive learning in KGR and propose a novel multi-level interactive contrastive learning mechanism, to alleviate the aforementioned challenges.		 DING ZOU et. al.
2022 8 CorpusBrain: Pre-train A Generative Retrieval Model for Knowledge-Intensive Language Tasks
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Highlight: Inspired by recent efforts in constructing model-based IR models, we propose to replace the traditional multi-step search pipeline with a novel single-step generative model, which can dramatically simplify the search process and be optimized in an end-to-end manner.		 JIANGUI CHEN et. al.
2022 9 TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis
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Highlight: In this paper, we propose a Time-Frequency analysis based time series Anomaly Detection model, or TFAD for short, to exploit both time and frequency domains for performance improvement.		 Chaoli Zhang; Tian Zhou; Qingsong Wen; Liang Sun;
2022 10 Contrastive Cross-Domain Sequential Recommendation
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Highlight: However, such a pipeline and implicit solution can be severely limited by the bottleneck of the designed transferring module, and ignores to consider inter-sequence item relationships. In this paper, we propose C2DSR to tackle the above problems to capture precise user preferences.		 Jiangxia Cao; Xin Cong; Jiawei Sheng; Tingwen Liu; Bin Wang;
2022 11 Disentangled Contrastive Learning for Social Recommendation
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Highlight: However, such an approach may fail to model the users’ heterogeneous behavior patterns in two domains, impairing the expressiveness of user representations. In this work, to address such limitation, we propose a novel Disentangled contrastive learning framework for social Recommendations (DcRec).		 JIAHAO WU et. al.
2022 12 SVD-GCN: A Simplified Graph Convolution Paradigm for Recommendation
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Highlight: By simplifying LightGCN, we show the close connection between GCN-based and low-rank methods such as Singular Value Decomposition (SVD) and Matrix Factorization (MF), where stacking graph convolution layers is to learn a low-rank representation by emphasizing (suppressing) components with larger (smaller) singular values. Based on this observation, we replace the core design of GCN-based methods with a flexible truncated SVD and propose a simplified GCN learning paradigm dubbed SVD-GCN, which only exploits K-largest singular vectors for recommendation.		 Shaowen Peng; Kazunari Sugiyama; Tsunenori Mine;
2022 13 Real-time Short Video Recommendation on Mobile Devices
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Highlight: However, as users continue to watch videos and feedback, the changing context leads the ranking of the server-side recommendation system inaccurate. In this paper, we propose to deploy a short video recommendation framework on mobile devices to solve these problems.		 XUDONG GONG et. al.
2022 14 Imbalanced Graph Classification Via Graph-of-Graph Neural Networks
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Highlight: To this end, we introduce a novel framework, Graph-of-Graph Neural Networks (G2GNN), which alleviates the graph imbalance issue by deriving extra supervision globally from neighboring graphs and locally from stochastic augmentations of graphs.		 Yu Wang; Yuying Zhao; Neil Shah; Tyler Derr;
2022 15 Crowdsourced Fact-Checking at Twitter: How Does The Crowd Compare With Experts?
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Highlight: In this work, we study the first large-scale effort of crowdsourced fact-checking deployed in practice, started by Twitter with the Birdwatch program.		 Mohammed Saeed; Nicolas Traub; Maelle Nicolas; Gianluca Demartini; Paolo Papotti;
2021 1 RecBole: Towards A Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
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Highlight: In the light of this challenge, we propose a unified, comprehensive and efficient recommender system library called RecBole (pronounced as [rEk’[email protected]]), which provides a unified framework to develop and reproduce recommendation algorithms for research purpose.		 WAYNE XIN ZHAO et. al.
2021 2 UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation
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Abstract: With the recent success of graph convolutional networks (GCNs), they have been widely applied for recommendation, and achieved impressive performance gains. The core of GCNs lies …		 KELONG MAO et. al.
2021 3 Self-supervised Learning for Large-scale Item Recommendations
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Highlight: Inspired by the recent success in self-supervised representation learning research in both computer vision and natural language understanding, we propose a multi-task self-supervised learning (SSL) framework for large-scale item recommendations.		 TIANSHENG YAO et. al.
2021 4 ETA Prediction with Graph Neural Networks in Google Maps
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Highlight: Here we present a graph neural network estimator for estimated time of arrival (ETA) which we have deployed in production at Google Maps.		 AUSTIN DERROW-PINION et. al.
2021 5 AdaRNN: Adaptive Learning and Forecasting of Time Series
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Highlight: In this paper, we term this as Temporal Covariate Shift (TCS).		 YUNTAO DU et. al.
2021 6 PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models
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Highlight: We present PyTorch Geometric Temporal, a deep learning framework combining state-of-the-art machine learning algorithms for neural spatiotemporal signal processing.		 BENEDEK ROZEMBERCZKI et. al.
2021 7 A Unified View on Graph Neural Networks As Graph Signal Denoising
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Highlight: In this work, we establish mathematically that the aggregation processes in a group of representative GNN models including GCN, GAT, PPNP, and APPNP can be regarded as (approximately) solving a graph denoising problem with a smoothness assumption.		 YAO MA et. al.
2021 8 Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
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Highlight: Therefore, we propose to unify sequential patterns and temporal collaborative signals to improve the quality of recommendation, which is rather challenging.		 ZIWEI FAN et. al.
2021 9 Self-Supervised Graph Co-Training for Session-based Recommendation
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Abstract: Session-based recommendation targets next-item prediction by exploiting user behaviors within a short time period. Compared with other recommendation paradigms, session-based …		 Xin Xia; Hongzhi Yin; Junliang Yu; Yingxia Shao; Lizhen Cui;
2021 10 One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction
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Highlight: In this paper, we propose the Star Topology Adaptive Recommender (STAR) model to train a single model to serve all domains by leveraging data from all domains simultaneously, capturing the characteristics of each domain, and modeling the commonalities between different domains.		 XIANG-RONG SHENG et. al.
2021 11 SimpleX: A Simple and Strong Baseline for Collaborative Filtering
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Highlight: In this work, we show that the choice of loss function as well as negative sampling ratio is equivalently important.		 KELONG MAO et. al.
2021 12 DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction
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Abstract: Nowadays, with the rapid development of IoT (Internet of Things) and CPS (Cyber-Physical Systems) technologies, big spatiotemporal data are being generated from mobile phones, car …		 RENHE JIANG et. al.
2021 13 Counterfactual Explainable Recommendation
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Highlight: In this paper, we propose Counterfactual Explainable Recommendation (CountER), which takes the insights of counterfactual reasoning from causal inference for explainable recommendation.		 JUNTAO TAN et. al.
2021 14 TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark
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Highlight: To alleviate these problems, we present TwiBot-20, a massive Twitter bot detection benchmark, which contains 229,573 users, 33,488,192 tweets, 8,723,736 user property items and 455,958 follow relationships.		 Shangbin Feng; Herun Wan; Ningnan Wang; Jundong Li; Minnan Luo;
2021 15 Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation
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Highlight: In this paper, we propose a self-supervised hypergraph learning framework for group recommendation to achieve two goals: (1) capturing the intra- and inter-group interactions among users; (2) alleviating the data sparsity issue with the raw data itself.		 JUNWEI ZHANG et. al.
2020 1 S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization
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Highlight: To tackle this problem, we propose the model S3-Rec, which stands for Self-Supervised learning for Sequential Recommendation, based on the self-attentive neural architecture.		 KUN ZHOU et. al.
2020 2 SenticNet 6: Ensemble Application of Symbolic and Subsymbolic AI for Sentiment Analysis
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Highlight: In this work, we integrate top-down and bottom-up learning via an ensemble of symbolic and subsymbolic AI tools, which we apply to the interesting problem of polarity detection from text.		 Erik Cambria; Yang Li; Frank Z. Xing; Soujanya Poria; Kenneth Kwok;
2020 3 Enhancing Graph Neural Network-based Fraud Detectors Against Camouflaged Fraudsters
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Highlight: Alternatively, we propose a new model named CAmouflage-REsistant GNN (CARE-GNN), to enhance the GNN aggregation process with three unique modules against camouflages.		 YINGTONG DOU et. al.
2020 4 Characteristic Functions on Graphs: Birds of A Feather, from Statistical Descriptors to Parametric Models
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Highlight: In this paper, we propose a flexible notion of characteristic functions defined on graph vertices to describe the distribution of vertex features at multiple scales.		 Benedek Rozemberczki; Rik Sarkar;
2020 5 FANG: Leveraging Social Context for Fake News Detection Using Graph Representation
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Highlight: We propose Factual News Graph (FANG), a novel graphical social context representation and learning framework for fake news detection.		 Van-Hoang Nguyen; Kazunari Sugiyama; Preslav Nakov; Min-Yen Kan;
2020 6 Feedback Loop and Bias Amplification in Recommender Systems
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Highlight: In this paper, we propose a method for simulating the users interaction with the recommenders in an offline setting and study the impact of feedback loop on the popularity bias amplification of several recommendation algorithms.		 Masoud Mansoury; Himan Abdollahpouri; Mykola Pechenizkiy; Bamshad Mobasher; Robin Burke;
2020 7 Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction
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Highlight: In this paper, we tackle this problem by designing a new modeling paradigm, which we name as Search-based Interest Model (SIM).		 QI PI et. al.
2020 8 Detection of Novel Social Bots By Ensembles of Specialized Classifiers
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Highlight: To address these issues, we propose a new supervised learning method that trains classifiers specialized for each class of bots and combines their decisions through the maximum rule.		 Mohsen Sayyadiharikandeh; Onur Varol; Kai-Cheng Yang; Alessandro Flammini; Filippo Menczer;
2020 9 Multi-modal Knowledge Graphs for Recommender Systems
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Highlight: In this paper, we propose Multi-modal Knowledge Graph Attention Network (MKGAT) to better enhance recommender systems by leveraging multi-modal knowledge.		 RUI SUN et. al.
2020 10 ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research
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Highlight: In this work, we present ReCOVery, a repository designed and constructed to facilitate research on combating such information regarding COVID-19.		 Xinyi Zhou; Apurva Mulay; Emilio Ferrara; Reza Zafarani;
2020 11 Karate Club: An API Oriented Open-Source Python Framework for Unsupervised Learning on Graphs
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Highlight: We present Karate Club – a Python framework combining more than 30 state-of-the-art graph mining algorithms.		 Benedek Rozemberczki; Oliver Kiss; Rik Sarkar;
2020 12 Evaluating Stochastic Rankings with Expected Exposure
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Highlight: We introduce the concept of expected exposure as the average attention ranked items receive from users over repeated samples of the same query.		 Fernando Diaz; Bhaskar Mitra; Michael D. Ekstrand; Asia J. Biega; Ben Carterette;
2020 13 Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots
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Highlight: In this paper, we study the problem of employing pre-trained language models for multi-turn response selection in retrieval-based chatbots.		 JIA-CHEN GU et. al.
2020 14 Star Graph Neural Networks for Session-based Recommendation
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Highlight: We propose Star Graph Neural Networks with Highway Networks (SGNN-HN) for session-based recommendation.		 Zhiqiang Pan; Fei Cai; Wanyu Chen; Honghui Chen; Maarten de Rijke;
2020 15 ST-GRAT: A Novel Spatio-temporal Graph Attention Networks for Accurately Forecasting Dynamically Changing Road Speed
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Highlight: This paper proposes a novel spatio-temporal graph attention (ST-GRAT) that effectively captures the spatio-temporal dynamics in road networks.		 CHEONBOK PARK et. al.
2019 1 BERT4Rec: Sequential Recommendation With Bidirectional Encoder Representations From Transformer
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Highlight: \end enumerate* To address these limitations, we proposed a sequential recommendation model called BERT4Rec, which employs the deep bidirectional self-attention to model user behavior sequences.		 FEI SUN et. al.
2019 2 AutoInt: Automatic Feature Interaction Learning Via Self-Attentive Neural Networks
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Highlight: In this paper, we propose an effective and efficient method called the AutoInt to automatically learn the high-order feature interactions of input features.		 WEIPING SONG et. al.
2019 3 Enriching Pre-trained Language Model With Entity Information For Relation Classification
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Highlight: In this paper, we propose a model that both leverages the pre-trained BERT language model and incorporates information from the target entities to tackle the relation classification task.		 Shanchan Wu; Yifan He;
2019 4 Multi-Interest Network With Dynamic Routing For Recommendation At Tmall
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Highlight: In this paper, we approach the learning of user representations from a different view, by representing a user with multiple representation vectors encoding the different aspects of the user’s interests.		 CHAO LI et. al.
2019 5 Rethinking The Item Order In Session-based Recommendation With Graph Neural Networks
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Highlight: In this paper, therefore, we study the item transition pattern by constructing a session graph and propose a novel model which collaboratively considers the sequence order and the latent order in the session graph for a session-based recommender system.		 Ruihong Qiu; Jingjing Li; Zi Huang; Hongzhi YIn;
2019 6 CoLight: Learning Network-level Cooperation For Traffic Signal Control
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Highlight: To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication.		 HUA WEI et. al.
2019 7 Spam Review Detection With Graph Convolutional Networks
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Highlight: In this paper, we present our technical solutions to address these challenges.		 Ao Li; Zhou Qin; Runshi Liu; Yiqun Yang; Dong Li;
2019 8 DSANet: Dual Self-Attention Network For Multivariate Time Series Forecasting
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Highlight: In this paper, we propose a dual self-attention network (DSANet) for highly efficient multivariate time series forecasting, especially for dynamic-period or nonperiodic series.		 Siteng Huang; Donglin Wang; Xuehan Wu; Ao Tang;
2019 9 Meta-GNN: On Few-shot Node Classification In Graph Meta-learning
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Highlight: Towards this, we propose a novel graph meta-learning framework — Meta-GNN — to tackle the few-shot node classification problem in graph meta-learning settings.		 FAN ZHOU et. al.
2019 10 Fi-GNN: Modeling Feature Interactions Via Graph Neural Networks For CTR Prediction
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Highlight: In this work, we propose to represent the multi-field features in a graph structure intuitively, where each node corresponds to a feature field and different fields can interact through edges.		 Zekun Li; Zeyu Cui; Shu Wu; Xiaoyu Zhang; Liang Wang;
2019 11 Learning Phase Competition For Traffic Signal Control
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Highlight: In this paper, we propose a novel design called FRAP, which is based on the intuitive principle of phase competition in traffic signal control: when two traffic signals conflict, priority should be given to one with larger traffic movement (i.e., higher demand).		 GUANJIE ZHENG et. al.
2019 12 Semi-Supervised Learning For Cross-Domain Recommendation To Cold-Start Users
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Highlight: In this paper, we propose a novel CDR framework based on semi-supervised mapping, called SSCDR, which effectively learns the cross-domain relationship even in the case that only a few number of labeled data is available.		 SeongKu Kang; Junyoung Hwang; Dongha Lee; Hwanjo Yu;
2019 13 DTCDR: A Framework For Dual-Target Cross-Domain Recommendation
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Highlight: To this end, in this paper, we propose a new framework, DTCDR, for Dual-Target Cross-Domain Recommendation.		 Feng Zhu; Chaochao Chen; Yan Wang; Guanfeng Liu; Xiaolin Zheng;
2019 14 How Does BERT Answer Questions?: A Layer-Wise Analysis Of Transformer Representations
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Highlight: In order to better understand BERT and other Transformer-based models, we present a layer-wise analysis of BERT’s hidden states.		 Betty van Aken; Benjamin Winter; Alexander L�ser; Felix A. Gers;
2019 15 Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach
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Highlight: To that end, in this paper, we propose a novel framework called Hierarchical Attention-based Recurrent Neural Network (HARNN) for classifying documents into the most relevant categories level by level via integrating texts and the hierarchical category structure.		 WEI HUANG et. al.
2018 1 RippleNet: Propagating User Preferences On The Knowledge Graph For Recommender Systems
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Highlight: To address the limitations of existing embedding-based and path-based methods for knowledge-graph-aware recommendation, we propose RippleNet, an end-to-end framework that naturally incorporates the knowledge graph into recommender systems.		 HONGWEI WANG et. al.
2018 2 Recurrent Neural Networks With Top-k Gains For Session-based Recommendations
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Highlight: In this work we introduce novel ranking loss functions tailored to RNNs in the recommendation setting.		 Bal�zs Hidasi; Alexandros Karatzoglou;
2018 3 Towards Conversational Search And Recommendation: System Ask, User Respond
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Highlight: In this paper, we propose and evaluate a unified conversational search/recommendation framework, in an attempt to make the research problem doable under a standard formalization.		 Yongfeng Zhang; Xu Chen; Qingyao Ai; Liu Yang; W. Bruce Croft;
2018 4 CoNet: Collaborative Cross Networks For Cross-Domain Recommendation
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Highlight: In this paper, we propose a novel transfer learning approach for cross-domain recommendation by using neural networks as the base model.		 Guangneng Hu; Yu Zhang; Qiang Yang;
2018 5 Heterogeneous Graph Neural Networks For Malicious Account Detection
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Highlight: We present, GEM, the first heterogeneous graph neural network approach for detecting malicious accounts at Alipay, one of the world’s leading mobile cashless payment platform.		 ZIQI LIU et. al.
2018 6 REGAL: Representation Learning-based Graph Alignment
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Highlight: Motivated by recent advancements in node representation learning for single-graph tasks, we propose REGAL (REpresentation learning-based Graph ALignment), a framework that leverages the power of automatically-learned node representations to match nodes across different graphs.		 Mark Heimann; Haoming Shen; Tara Safavi; Danai Koutra;
2018 7 Rumor Detection With Hierarchical Social Attention Network
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Highlight: In this paper, we detect rumors by leveraging hierarchical representations at different levels and the social contexts.		 Han Guo; Juan Cao; Yazi Zhang; Junbo Guo; Jintao Li;
2018 8 Deep Autoencoder-like Nonnegative Matrix Factorization For Community Detection
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Highlight: Inspired by the unique feature representation learning capability of deep autoencoder, we propose a novel model, named Deep Autoencoder-like NMF (DANMF), for community detection.		 Fanghua Ye; Chuan Chen; Zibin Zheng;
2018 9 KAME: Knowledge-based Attention Model For Diagnosis Prediction In Healthcare
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Highlight: To address these issues, we propose KAME, an end-to-end, accurate and robust model for predicting patients’ future health information.		 FENGLONG MA et. al.
2018 10 Weakly-Supervised Neural Text Classification
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Highlight: In this paper, we propose a weakly-supervised method that addresses the lack of training data in neural text classification.		 Yu Meng; Jiaming Shen; Chao Zhang; Jiawei Han;
2018 11 From Neural Re-Ranking To Neural Ranking: Learning A Sparse Representation For Inverted Indexing
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Highlight: In this work, we propose a standalone neural ranking model (SNRM) by introducing a sparsity property to learn a latent sparse representation for each query and document.		 Hamed Zamani; Mostafa Dehghani; W. Bruce Croft; Erik Learned-Miller; Jaap Kamps;
2018 12 CFGAN: A Generic Collaborative Filtering Framework Based On Generative Adversarial Networks
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Highlight: In this paper, we propose a novel GAN-based collaborative filtering (CF) framework to provide higher accuracy in recommendation.		 Dong-Kyu Chae; Jin-Soo Kang; Sang-Wook Kim; Jung-Tae Lee;
2018 13 Real-Time Bidding With Multi-Agent Reinforcement Learning In Display Advertising
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Highlight: In this paper, we formulate bidding optimization with multi-agent reinforcement learning.		 JUNQI JIN et. al.
2018 14 Incorporating Corporation Relationship Via Graph Convolutional Neural Networks For Stock Price Prediction
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Highlight: In this paper, we propose to incorporate information of related corporations of a target company for its stock price prediction.		 Yingmei Chen; Zhongyu Wei; Xuanjing Huang;
2018 15 ANR: Aspect-based Neural Recommender
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Highlight: In this paper, we propose a novel end-to-end Aspect-based Neural Recommender (ANR) to perform aspect-based representation learning for both users and items via an attention-based component.		 Jin Yao Chin; Kaiqi Zhao; Shafiq Joty; Gao Cong;
2017 1 Neural Attentive Session-based Recommendation
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Highlight: In this paper, we propose a novel neural networks framework, i.e., Neural Attentive Recommendation Machine (NARM), to tackle this problem.		 JING LI et. al.
2017 2 CSI: A Hybrid Deep Model For Fake News Detection
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Highlight: In this work, we propose a model that combines all three characteristics for a more accurate and automated prediction.		 Natali Ruchansky; Sungyong Seo; Yan Liu;
2017 3 HIN2Vec: Explore Meta-paths In Heterogeneous Information Networks For Representation Learning
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Highlight: In this paper, we propose a novel representation learning framework, namely HIN2Vec, for heterogeneous information networks (HINs).		 Tao-yang Fu; Wang-Chien Lee; Zhen Lei;
2017 4 FA*IR: A Fair Top-k Ranking Algorithm
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Highlight: In this work, we define and solve the Fair Top-k Ranking problem, in which we want to determine a subset of k candidates from a large pool of n » k candidates, maximizing utility (i.e., select the "best" candidates) subject to group fairness criteria.		 MEIKE ZEHLIKE et. al.
2017 5 MGAE: Marginalized Graph Autoencoder For Graph Clustering
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Highlight: In this paper, we propose a novel marginalized graph autoencoder (MGAE) algorithm for graph clustering.		 Chun Wang; Shirui Pan; Guodong Long; Xingquan Zhu; Jing Jiang;
2017 6 Learning Community Embedding With Community Detection And Node Embedding On Graphs
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Highlight: In this paper, we study an important yet largely under-explored setting of graph embedding, i.e., embedding communities instead of each individual nodes.		 Sandro Cavallari; Vincent W. Zheng; Hongyun Cai; Kevin Chen-Chuan Chang; Erik Cambria;
2017 7 Attributed Network Embedding For Learning In A Dynamic Environment
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Highlight: In this paper, we tackle this problem by proposing a novel dynamic attributed network embedding framework – DANE.		 JUNDONG LI et. al.
2017 8 Joint Representation Learning For Top-N Recommendation With Heterogeneous Information Sources
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Highlight: In this work, we propose a Joint Representation Learning (JRL) framework for top-N recommendation.		 Yongfeng Zhang; Qingyao Ai; Xu Chen; W. Bruce Croft;
2017 9 DeepRank: A New Deep Architecture For Relevance Ranking In Information Retrieval
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Highlight: In this paper we propose a new deep learning architecture, namely DeepRank, to simulate the above human judgment process.		 LIANG PANG et. al.
2017 10 Fast And Accurate Time Series Classification With WEASEL
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Highlight: In this paper, we present WEASEL (Word ExtrAction for time SEries cLassification), a novel TSC method which is both fast and accurate.		 Patrick Schäfer; Ulf Leser;
2017 11 DeepHawkes: Bridging The Gap Between Prediction And Understanding Of Information Cascades
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Highlight: In this paper, we propose DeepHawkes to combat the defects of existing methods, leveraging end-to-end deep learning to make an analogy to interpretable factors of Hawkes process — a widely-used generative process to model information cascade.		 Qi Cao; Huawei Shen; Keting Cen; Wentao Ouyang; Xueqi Cheng;
2017 12 SERM: A Recurrent Model For Next Location Prediction In Semantic Trajectories
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Highlight: We propose a method named semantics-enriched recurrent model (SERM).		 Di Yao; Chao Zhang; Jianhui Huang; Jingping Bi;
2017 13 An Attention-based Collaboration Framework For Multi-View Network Representation Learning
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Highlight: We propose a multi-view representation learning approach, which promotes the collaboration of different views and lets them vote for the robust representations.		 MENG QU et. al.
2017 14 Aspect-level Sentiment Classification With HEAT (HiErarchical ATtention) Network
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Highlight: To solve this problem, we propose a HiErarchical ATtention (HEAT) network for aspect-level sentiment classification.		 JIAJUN CHENG et. al.
2017 15 FUSION: An Online Method For Multistream Classification
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Highlight: In this paper, we propose an efficient solution for multistream classification by fusing drift detection into online data shift adaptation.		 AHSANUL HAQUE et. al.
2016 1 A Deep Relevance Matching Model For Ad-hoc Retrieval
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Highlight: In this paper, we propose a novel deep relevance matching model (DRMM) for ad-hoc retrieval.		 Jiafeng Guo; Yixing Fan; Qingyao Ai; W. Bruce Croft;
2016 2 Learning Graph-based POI Embedding For Location-based Recommendation
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Highlight: To address these challenges, we stand on recent advances in embedding learning techniques and propose a generic graph-based embedding model, called GE, in this paper.		 MIN XIE et. al.
2016 3 ANMM: Ranking Short Answer Texts With Attention-Based Neural Matching Model
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Highlight: In this paper, we propose an attention based neural matching model for ranking short answer text.		 Liu Yang; Qingyao Ai; Jiafeng Guo; W. Bruce Croft;
2016 4 LogMine: Fast Pattern Recognition For Log Analytics
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Highlight: We propose a method, named LogMine, that extracts high quality patterns for a given set of log messages.		 HOSSEIN HAMOONI et. al.
2016 5 Query Expansion Using Word Embeddings
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Highlight: We present a suite of query expansion methods that are based on word embeddings.		 Saar Kuzi; Anna Shtok; Oren Kurland;
2016 6 Credibility Assessment Of Textual Claims On The Web
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Highlight: For inference, our method leverages the joint interaction between the language of articles about the claim and the reliability of the underlying web sources.		 Kashyap Popat; Subhabrata Mukherjee; Jannik Strötgen; Gerhard Weikum;
2016 7 Feature Driven And Point Process Approaches For Popularity Prediction
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Highlight: From these observations, we argue that future work on popularity prediction should compare across feature-driven and generative modeling approaches in both classification and regression tasks.		 Swapnil Mishra; Marian-Andrei Rizoiu; Lexing Xie;
2016 8 Noise-Contrastive Estimation For Answer Selection With Deep Neural Networks
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Highlight: Unlike previous work which treats this task as a straightforward pointwise classification problem, we model this problem as a ranking task and propose a pairwise ranking approach that can directly exploit existing pointwise neural network models as base components.		 Jinfeng Rao; Hua He; Jimmy Lin;
2016 9 Social Recommendation With Strong And Weak Ties
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Highlight: In this work, we study the effects of distinguishing strong and weak ties in social recommendation.		 Xin Wang; Wei Lu; Martin Ester; Can Wang; Chun Chen;
2016 10 Learning Latent Vector Spaces For Product Search
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Highlight: We introduce a novel latent vector space model that jointly learns the latent representations of words, e-commerce products and a mapping between the two without the need for explicit annotations.		 Christophe Van Gysel; Maarten de Rijke; Evangelos Kanoulas;
2016 11 Retweet Prediction With Attention-based Deep Neural Network
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Highlight: In this work, we proposed a novel attention-based deep neural network to incorporate contextual and social information for this task. To train and evaluate the proposed methods, we also constructed a large dataset collected from Twitter.		 Qi Zhang; Yeyun Gong; Jindou Wu; Haoran Huang; Xuanjing Huang;
2016 12 LambdaFM: Learning Optimal Ranking With Factorization Machines Using Lambda Surrogates
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Highlight: In this paper, we demonstrate, both theoretically and empirically, PRFM models usually lead to non-optimal item recommendation results due to such a mismatch.		 FAJIE YUAN et. al.
2016 13 To Click Or Not To Click: Automatic Selection Of Beautiful Thumbnails From Videos
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Highlight: We present an automatic thumbnail selection system that exploits two important characteristics commonly associated with meaningful and attractive thumbnails: high relevance to video content and superior visual aesthetic quality.		 Yale Song; Miriam Redi; Jordi Vallmitjana; Alejandro Jaimes;
2016 14 Survival Analysis Based Framework For Early Prediction Of Student Dropouts
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Highlight: In this paper, we develop a survival analysis framework for early prediction of student dropout using Cox proportional hazards regression model (Cox).		 Sattar Ameri; Mahtab J. Fard; Ratna B. Chinnam; Chandan K. Reddy;
2016 15 Learning Points And Routes To Recommend Trajectories
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Highlight: We propose a new F1 score on pairs of POIs that capture the order of visits.		 Dawei Chen; Cheng Soon Ong; Lexing Xie;
2015 1 GraRep: Learning Graph Representations With Global Structural Information
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Highlight: In this paper, we present {GraRep}, a novel model for learning vertex representations of weighted graphs.		 Shaosheng Cao; Wei Lu; Qiongkai Xu;
2015 2 Detect Rumors Using Time Series Of Social Context Information On Microblogging Websites
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Highlight: In this study, we propose a novel approach to capture the temporal characteristics of these features based on the time series of rumor’s lifecycle, for which time series modeling technique is applied to incorporate various social context information.		 Jing Ma; Wei Gao; Zhongyu Wei; Yueming Lu; Kam-Fai Wong;
2015 3 A Hierarchical Recurrent Encoder-Decoder For Generative Context-Aware Query Suggestion
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Highlight: We present a novel hierarchical recurrent encoder-decoder architecture that makes possible to account for sequences of previous queries of arbitrary lengths.		 ALESSANDRO SORDONI et. al.
2015 4 TriRank: Review-aware Explainable Recommendation By Modeling Aspects
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Highlight: Aside from users’ ratings, their affiliated reviews often provide the rationale for their ratings and identify what aspects of the item they cared most about.		 Xiangnan He; Tao Chen; Min-Yen Kan; Xiao Chen;
2015 5 Deep Collaborative Filtering Via Marginalized Denoising Auto-encoder
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Highlight: In particular, we propose a general deep architecture for CF by integrating matrix factorization with deep feature learning.		 Sheng Li; Jaya Kawale; Yun Fu;
2015 6 Short Text Similarity With Word Embeddings
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Highlight: We propose to go from word-level to text-level semantics by combining insights from methods based on external sources of semantic knowledge with word embeddings.		 Tom Kenter; Maarten de Rijke;
2015 7 Learning To Represent Knowledge Graphs With Gaussian Embedding
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Highlight: Therefore, this paper switches to density-based embedding and propose KG2E for explicitly modeling the certainty of entities and relations, which learn the representations of KGs in the space of multi-dimensional Gaussian distributions.		 Shizhu He; Kang Liu; Guoliang Ji; Jun Zhao;
2015 8 Real-time Rumor Debunking On Twitter
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Highlight: In this paper, we propose the first real time rumor debunking algorithm for Twitter.		 Xiaomo Liu; Armineh Nourbakhsh; Quanzhi Li; Rui Fang; Sameena Shah;
2015 9 Semantic Path Based Personalized Recommendation On Weighted Heterogeneous Information Networks
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Highlight: In this paper, we are the first to propose the weighted HIN and weighted meta path concepts to subtly depict the path semantics through distinguishing different link attribute values.		 CHUAN SHI et. al.
2015 10 More Accurate Question Answering On Freebase
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Highlight: We evaluate our system, called Aqqu, on two standard benchmarks, Free917 and WebQuestions, improving the previous best result for each benchmark considerably.		 Hannah Bast; Elmar Haussmann;
2015 11 Detecting Check-worthy Factual Claims In Presidential Debates
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Highlight: Specifically, we prepared a U.S. presidential debate dataset and built classification models to distinguish check-worthy factual claims from non-factual claims and unimportant factual claims.		 Naeemul Hassan; Chengkai Li; Mark Tremayne;
2015 12 Extracting Situational Information From Microblogs During Disaster Events: A Classification-Summarization Approach
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Highlight: The proposed framework takes into consideration the typicalities pertaining to disaster events where (i) the same tweet often contains a mixture of situational and non-situational information, and (ii) certain numerical information, such as number of casualties, vary rapidly with time, and thus achieves superior performance compared to state-of-the-art tweet summarization approaches.		 Koustav Rudra; Subham Ghosh; Niloy Ganguly; Pawan Goyal; Saptarshi Ghosh;
2015 13 HDRF: Stream-Based Partitioning For Power-Law Graphs
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Highlight: In this paper, we propose High-Degree (are) Replicated First (HDRF), a novel streaming vertex-cut graph partitioning algorithm that effectively exploits skewed degree distributions by explicitly taking into account vertex degree in the placement decision.		 Fabio Petroni; Leonardo Querzoni; Khuzaima Daudjee; Shahin Kamali; Giorgio Iacoboni;
2015 14 A Convolutional Click Prediction Model
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Highlight: In this work, we propose a novel model, Convolutional Click Prediction Model (CCPM), based on convolution neural network.		 Qiang Liu; Feng Yu; Shu Wu; Liang Wang;
2015 15 Unsupervised Streaming Feature Selection In Social Media
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Highlight: In this paper, we study a novel problem to conduct unsupervised streaming feature selection for social media data.		 Jundong Li; Xia Hu; Jiliang Tang; Huan Liu;
2014 1 A Latent Semantic Model With Convolutional-Pooling Structure For Information Retrieval
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Highlight: In this paper, we propose a new latent semantic model that incorporates a convolutional-pooling structure over word sequences to learn low-dimensional, semantic vector representations for search queries and Web documents.		 Yelong Shen; Xiaodong He; Jianfeng Gao; Li Deng; Grégoire Mesnil;
2014 2 Leveraging Social Connections To Improve Personalized Ranking For Collaborative Filtering
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Highlight: Using social connections to better estimate users’ rankings of products is the task we consider in this paper.		 Tong Zhao; Julian McAuley; Irwin King;
2014 3 Exploiting Geographical Neighborhood Characteristics For Location Recommendation
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Highlight: In this paper, we are interested in exploiting geographical characteristics from a location perspective, by modeling the geographical neighborhood of a location.		 Yong Liu; Wei Wei; Aixin Sun; Chunyan Miao;
2014 4 Graph-based Point-of-interest Recommendation With Geographical And Temporal Influences
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Highlight: In this paper, we focus on the problem of time-aware POI recommendation, which aims at recommending a list of POIs for a user to visit at a given time.		 Quan Yuan; Gao Cong; Aixin Sun;
2014 5 Sketch-based Influence Maximization And Computation: Scaling Up With Guarantees
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Highlight: Basic computational problems in the study of diffusion are influence queries (determining the potency of a specified seed set of nodes) and Influence Maximization (identifying the most influential seed set of a given size).		 Edith Cohen; Daniel Delling; Thomas Pajor; Renato F. Werneck;
2014 6 RC-NET: A General Framework For Incorporating Knowledge Into Word Representations
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Highlight: Hence, in this paper, we introduce a novel framework called RC-NET to leverage both the relational and categorical knowledge to produce word representations of higher quality.		 CHANG XU et. al.
2014 7 Medical Semantic Similarity With A Neural Language Model
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Highlight: In this paper, we explore a variation of neural language models that can learn on concepts taken from structured ontologies and extracted from free-text, rather than directly from terms in free-text.		 Lance De Vine; Guido Zuccon; Bevan Koopman; Laurianne Sitbon; Peter Bruza;
2014 8 Question Retrieval With High Quality Answers In Community Question Answering
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Highlight: To address these problems, we propose a supervised question-answer topic modeling approach.		 Kai Zhang; Wei Wu; Haocheng Wu; Zhoujun Li; Ming Zhou;
2014 9 Canonicalizing Open Knowledge Bases
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Highlight: In this paper, we present an approach based on machine learning methods that can canonicalize such Open IE triples, by clustering synonymous names and phrases.		 Luis Galárraga; Geremy Heitz; Kevin Murphy; Fabian M. Suchanek;
2014 10 Supporting Complex Search Tasks
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Highlight: We present methods to automatically identify and recommend sub-tasks to help people explore and accomplish complex search tasks.		 Ahmed Hassan Awadallah; Ryen W. White; Patrick Pantel; Susan T. Dumais; Yi-Min Wang;
2014 11 Concept-based Short Text Classification And Ranking
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Highlight: In this paper, we propose using “Bag-of-Concepts” in short text representation, aiming to avoid the surface mismatching and handle the synonym and polysemy problem.		 Fang Wang; Zhongyuan Wang; Zhoujun Li; Ji-Rong Wen;
2014 12 Influence Maximization Over Large-Scale Social Networks: A Bounded Linear Approach
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Highlight: To this end, in this paper, we provide a bounded linear approach for influence computation and influence maximization.		 QI LIU et. al.
2014 13 Meta-Path-Based Ranking With Pseudo Relevance Feedback On Heterogeneous Graph For Citation Recommendation
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Highlight: By using learning-to-rank, we integrate 18 different meta-path-based ranking features to derive the final ranking scores for candidate cited papers.		 Xiaozhong Liu; Yingying Yu; Chun Guo; Yizhou Sun;
2014 14 Robust Entity Linking Via Random Walks
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Highlight: In this work, we present a novel approach that is guided by a natural notion of semantic similarity which is less amenable to such bias.		 Zhaochen Guo; Denilson Barbosa;
2014 15 Twitter Opinion Topic Model: Extracting Product Opinions From Tweets By Leveraging Hashtags And Sentiment Lexicon
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Highlight: In this paper, we propose an LDA-based opinion model named Twitter Opinion Topic Model (TOTM) for opinion mining and sentiment analysis.		 Kar Wai Lim; Wray Buntine;
2013 1 Learning Deep Structured Semantic Models For Web Search Using Clickthrough Data
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Highlight: In this study we strive to develop a series of new latent semantic models with a deep structure that project queries and documents into a common low-dimensional space where the relevance of a document given a query is readily computed as the distance between them.		 PO-SEN HUANG et. al.
2013 2 Inferring Anchor Links Across Multiple Heterogeneous Social Networks
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Highlight: In this paper, we study the problem of anchor link prediction across multiple heterogeneous social networks, i.e., discovering the correspondence among different accounts of the same user.		 Xiangnan Kong; Jiawei Zhang; Philip S. Yu;
2013 3 Personalized Point-of-interest Recommendation By Mining Users’ Preference Transition
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Highlight: In this work, we propose a novel category-aware POI recommendation model, which exploits the transition patterns of users’ preference over location categories to improve location recommendation accuracy.		 Xin Liu; Yong Liu; Karl Aberer; Chunyan Miao;
2013 4 Building A Large-scale Corpus For Evaluating Event Detection On Twitter
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Highlight: In this paper, we propose a methodology for the creation of an event detection corpus. Specifically, we first create a new corpus that covers a period of 4 weeks and contains over 120 million tweets, which we make available for research.		 Andrew J. McMinn; Yashar Moshfeghi; Joemon M. Jose;
2013 5 CQArank: Jointly Model Topics And Expertise In Community Question Answering
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Highlight: To tackle this cluster of closely related problems in a principled approach, we proposed Topic Expertise Model (TEM), a novel probabilistic generative model with GMM hybrid, to jointly model topics and expertise by integrating textual content model and link structure analysis.		 LIU YANG et. al.
2013 6 StaticGreedy: Solving The Scalability-accuracy Dilemma In Influence Maximization
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Highlight: Motivated by this critical finding, we propose a static greedy algorithm, named StaticGreedy, to strictly guarantee the submodularity of influence spread function during the seed selection process.		 Suqi Cheng; Huawei Shen; Junming Huang; Guoqing Zhang; Xueqi Cheng;
2013 7 Overlapping Community Detection Using Seed Set Expansion
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Highlight: In this paper, we propose an efficient overlapping community detection algorithm using a seed set expansion approach.		 Joyce Jiyoung Whang; David F. Gleich; Inderjit S. Dhillon;
2013 8 Interactive Collaborative Filtering
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Highlight: In this paper, we study collaborative filtering (CF) in an interactive setting, in which a recommender system continuously recommends items to individual users and receives interactive feedback.		 Xiaoxue Zhao; Weinan Zhang; Jun Wang;
2013 9 Location Prediction In Social Media Based On Tie Strength
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Highlight: We propose a novel network-based approach for location estimation in social media that integrates evidence of the social tie strength between users for improved location estimation.		 Jeffrey McGee; James Caverlee; Zhiyuan Cheng;
2013 10 Graph-of-word And TW-IDF: New Approach To Ad Hoc IR
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Highlight: In this paper, we introduce novel document representation (graph-of-word) and retrieval model (TW-IDF) for ad hoc IR.		 François Rousseau; Michalis Vazirgiannis;
2013 11 Location Recommendation For Out-of-town Users In Location-based Social Networks
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Highlight: In this paper, we study the issues in making location recommendations for out-of-town users by taking into account user preference, social influence and geographical proximity.		 Gregory Ference; Mao Ye; Wang-Chien Lee;
2013 12 Automatic Ad Format Selection Via Contextual Bandits
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Highlight: To balance exploration with exploitation, we pose automatic layout selection as a contextual bandit problem.		 Liang Tang; Romer Rosales; Ajit Singh; Deepak Agarwal;
2013 13 Uncovering Collusive Spammers In Chinese Review Websites
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Highlight: Empirical analysis, on recently crawled product reviews from a popular Chinese e-commerce website, reveals the failure of many state-of-the-art spam indicators on detecting collusive spammers.		 Chang Xu; Jie Zhang; Kuiyu Chang; Chong Long;
2013 14 Re-ranking For Joint Named-entity Recognition And Linking
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Highlight: We present a joint model for NER and EL, called NEREL, that takes a large set of candidate mentions from typical NER systems and a large set of candidate entity links from EL systems, and ranks the candidate mention-entity pairs together to make joint predictions.		 Avirup Sil; Alexander Yates;
2013 15 On Popularity Prediction Of Videos Shared In Online Social Networks
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Highlight: In this paper, we present an initial study on the popularity prediction of videos propagated in OSNs along friendship links.		 Haitao Li; Xiaoqiang Ma; Feng Wang; Jiangchuan Liu; Ke Xu;
2012 1 Mining High Utility Itemsets Without Candidate Generation
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Highlight: In this paper, we propose an algorithm, called HUI-Miner (High Utility Itemset Miner), for high utility itemset mining.		 Mengchi Liu; Junfeng Qu;
2012 2 Twevent: Segment-based Event Detection From Tweets
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Highlight: In this paper, we propose a segment-based event detection system for tweets, called Twevent.		 Chenliang Li; Aixin Sun; Anwitaman Datta;
2012 3 Social Contextual Recommendation
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Highlight: In this paper, we investigate social recommendation on the basis of psychology and sociology studies, which exhibit two important factors: individual preference and interpersonal influence.		 MENG JIANG et. al.
2012 4 Detecting Offensive Tweets Via Topical Feature Discovery Over A Large Scale Twitter Corpus
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Highlight: In this paper, we propose a novel semi-supervised approach for detecting profanity-related offensive content in Twitter.		 Guang Xiang; Bin Fan; Ling Wang; Jason Hong; Carolyn Rose;
2012 5 Gelling, And Melting, Large Graphs By Edge Manipulation
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Highlight: So far, previous studies have mostly focused on removing or inoculating nodes to achieve the desired outcome.		 Hanghang Tong; B. Aditya Prakash; Tina Eliassi-Rad; Michalis Faloutsos; Christos Faloutsos;
2012 6 GSCorr: Modeling Geo-social Correlations For New Check-ins On Location-based Social Networks
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Highlight: In this paper, we propose to utilize the social network information for solving the "cold start" location prediction problem, with a geo-social correlation model to capture social correlations on LBSNs considering social networks and geographical distance.		 Huiji Gao; Jiliang Tang; Huan Liu;
2012 7 KORE: Keyphrase Overlap Relatedness For Entity Disambiguation
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Highlight: For efficiency, we have developed approximation techniques based on min-hash sketches and locality-sensitive hashing.		 Johannes Hoffart; Stephan Seufert; Dat Ba Nguyen; Martin Theobald; Gerhard Weikum;
2012 8 Prediction Of Retweet Cascade Size Over Time
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Highlight: In this paper we try to forecast how many retweets a given tweet will gain during a fixed time period.		 ANDREY KUPAVSKII et. al.
2012 9 On The Design Of LDA Models For Aspect-based Opinion Mining
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Highlight: In this paper, we present a set of design guidelines for aspect-based opinion mining by discussing a series of increasingly sophisticated LDA models.		 Samaneh Moghaddam; Martin Ester;
2012 10 Meta Path-based Collective Classification In Heterogeneous Information Networks
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Highlight: In this paper, we focus on studying the collective classification problem in heterogeneous networks, which involves multiple types of data objects interconnected by multiple types of links.		 Xiangnan Kong; Philip S. Yu; Ying Ding; David J. Wild;
2012 11 PARMA: A Parallel Randomized Algorithm For Approximate Association Rules Mining In MapReduce
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Highlight: We address this issue by proposing PARMA, a parallel algorithm for the MapReduce framework, which scales well with the size of the dataset (as number of transactions) while minimizing data replication and communication cost.		 Matteo Riondato; Justin A. DeBrabant; Rodrigo Fonseca; Eli Upfal;
2012 12 Deco: Declarative Crowdsourcing
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Highlight: We describe Deco’s data model, query language, and our prototype.		 Aditya Ganesh Parameswaran; Hyunjung Park; Hector Garcia-Molina; Neoklis Polyzotis; Jennifer Widom;
2012 13 Exploring Personal Impact For Group Recommendation
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Highlight: In this paper, we study the group recommendation problem, i.e., making recommendations to a group of people in social networking services.		 Xingjie Liu; Yuan Tian; Mao Ye; Wang-Chien Lee;
2012 14 Recommending Citations: Translating Papers Into References
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Highlight: Using this, we propose a method that "translates" research papers into references.		 WENYI HUANG et. al.
2012 15 Fast And Reliable Anomaly Detection In Categorical Data
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Highlight: We introduce COMPREX, a new approach for identifying anomalies using pattern-based compression.		 Leman Akoglu; Hanghang Tong; Jilles Vreeken; Christos Faloutsos;
2011 1 Topic Sentiment Analysis In Twitter: A Graph-based Hashtag Sentiment Classification Approach
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Highlight: In this paper, instead of presenting the sentiment polarity of each tweet relevant to the topic, we focus our study on hashtag-level sentiment classification.		 Xiaolong Wang; Furu Wei; Xiaohua Liu; Ming Zhou; Ming Zhang;
2011 2 Robust Nonnegative Matrix Factorization Using L21-norm
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Highlight: In this paper, we propose a robust formulation of NMF using L21 norm loss function.		 Deguang Kong; Chris Ding; Heng Huang;
2011 3 Transferring Topical Knowledge From Auxiliary Long Texts For Short Text Clustering
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Highlight: In this article, we present a novel approach to cluster short text messages via transfer learning from auxiliary long text data.		 Ou Jin; Nathan N. Liu; Kai Zhao; Yong Yu; Qiang Yang;
2011 4 Jasmine: A Real-time Local-event Detection System Based On Geolocation Information Propagated To Microblogs
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Highlight: Therefore, we propose an automatic geotagging method that identifies the location of non-geotagged documents.		 Kazufumi Watanabe; Masanao Ochi; Makoto Okabe; Rikio Onai;
2011 5 LogSig: Generating System Events From Raw Textual Logs
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Highlight: In this paper, we propose a message signature based algorithm logSig to generate system events from textual log messages.		 Liang Tang; Tao Li; Chang-Shing Perng;
2011 6 User Oriented Tweet Ranking: A Filtering Approach To Microblogs
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Highlight: In this paper, we propose a personalized tweet ranking method, leveraging the use of retweet behavior, to bring more important tweets forward.		 Ibrahim Uysal; W. Bruce Croft;
2011 7 Personalizing Web Search Results By Reading Level
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Highlight: We describe models and algorithms to address the three key problems in improving relevance for search using reading difficulty: estimating user proficiency, estimating result difficulty, and re-ranking based on the difference between user and result reading level profiles.		 Kevyn Collins-Thompson; Paul N. Bennett; Ryen W. White; Sebastian de la Chica; David Sontag;
2011 8 Discovering Top-k Teams Of Experts With/without A Leader In Social Networks
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Highlight: We propose two communication cost functions designed for two types of communication structures. We introduce the problem of finding a team of experts with a leader.		 Mehdi Kargar; Aijun An;
2011 9 Ontology-based Data Management
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Abstract: Ontology-based data management aims at accessing and using data by means of an ontology, i.e., a conceptual representation of the domain of interest in the underlying information …		 Maurizio Lenzerini;
2011 10 Citation Count Prediction: Learning To Estimate Future Citations For Literature
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Highlight: In this paper, we use the citations as a measurement for the popularity among researchers and study the interesting problem of Citation Count Prediction (CCP) to examine the characteristics for popularity.		 Rui Yan; Jie Tang; Xiaobing Liu; Dongdong Shan; Xiaoming Li;
2011 11 Sentiment Classification Based On Supervised Latent N-gram Analysis
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Highlight: In this paper, we propose an efficient embedding for modeling higher-order (n-gram) phrases that projects the n-grams to low-dimensional latent semantic space, where a classification function can be defined.		 Dmitriy Bespalov; Bing Bai; Yanjun Qi; Ali Shokoufandeh;
2011 12 Who Will Follow You Back?: Reciprocal Relationship Prediction
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Highlight: Employing Twitter as a source for our experimental data, we propose a learning framework to formulate the problem of reciprocal relationship prediction into a graphical model.		 John Hopcroft; Tiancheng Lou; Jie Tang;
2011 13 Exploiting Longer Cycles For Link Prediction In Signed Networks
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Highlight: We consider the problem of link prediction in signed networks.		 Kai-Yang Chiang; Nagarajan Natarajan; Ambuj Tewari; Inderjit S. Dhillon;
2011 14 Worker Types And Personality Traits In Crowdsourcing Relevance Labels
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Highlight: In this paper, we use behavioral observations (HIT completion time, fraction of useful labels, label accuracy) to define five worker types: Spammer, Sloppy, Incompetent, Competent, Diligent.		 Gabriella Kazai; Jaap Kamps; Natasa Milic-Frayling;
2011 15 Temporal Link Prediction By Integrating Content And Structure Information
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Highlight: In this paper we address the problem of temporal link prediction, i.e., predicting the apparition of new links, in time-evolving networks.		 Sheng Gao; Ludovic Denoyer; Patrick Gallinari;
2010 1 You Are Where You Tweet: A Content-based Approach To Geo-locating Twitter Users
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Highlight: We propose and evaluate a probabilistic framework for estimating a Twitter user’s city-level location based purely on the content of the user’s tweets, even in the absence of any other geospatial cues.		 Zhiyuan Cheng; James Caverlee; Kyumin Lee;
2010 2 TAGME: On-the-fly Annotation Of Short Text Fragments (by Wikipedia Entities)
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Highlight: We designed and implemented TAGME, a system that is able to efficiently and judiciously augment a plain-text with pertinent hyperlinks to Wikipedia pages.		 Paolo Ferragina; Ugo Scaiella;
2010 3 Detecting Product Review Spammers Using Rating Behaviors
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Highlight: This paper aims to detect users generating spam reviews or review spammers.		 Ee-Peng Lim; Viet-An Nguyen; Nitin Jindal; Bing Liu; Hady Wirawan Lauw;
2010 4 Classifying Sentiment In Microblogs: Is Brevity An Advantage?
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Highlight: In this work we examine the hypothesis that it is easier to classify the sentiment in these short form documents than in longer form documents.		 Adam Bermingham; Alan F. Smeaton;
2010 5 Finding Unusual Review Patterns Using Unexpected Rules
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Highlight: We formulate the problem as finding unexpected rules.		 Nitin Jindal; Bing Liu; Ee-Peng Lim;
2010 6 Travel Route Recommendation Using Geotags In Photo Sharing Sites
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Highlight: In this paper, we propose a travel route recommendation method that makes use of the photographers’ histories as held by Flickr.		 Takeshi Kurashima; Tomoharu Iwata; Go Irie; Ko Fujimura;
2010 7 Mining Topic-level Influence In Heterogeneous Networks
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Highlight: To address the problem, we propose a generative graphical model which utilizes the heterogeneous link information and the textual content associated with each node in the network to mine topic-level direct influence.		 Lu Liu; Jie Tang; Jiawei Han; Meng Jiang; Shiqiang Yang;
2010 8 Understanding Retweeting Behaviors In Social Networks
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Highlight: In this paper, we perform an interesting analysis for the problem on Twitter.		 ZI YANG et. al.
2010 9 Detecting Controversial Events From Twitter
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Highlight: This paper addresses the task of identifying controversial events using Twitter as a starting point: we propose 3 models for this task and report encouraging initial results.		 Ana-Maria Popescu; Marco Pennacchiotti;
2010 10 Opinion Digger: An Unsupervised Opinion Miner From Unstructured Product Reviews
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Highlight: We propose an unsupervised method, called Opinion Digger, which extracts important aspects of a product and determines the overall consumer’s satisfaction for each, by estimating a rating in the range from 1 to 5.		 Samaneh Moghaddam; Martin Ester;
2010 11 Predicting Short-term Interests Using Activity-based Search Context
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Highlight: In this paper, we describe a study in which we developed and evaluated user interest models for the current query, its context (from pre-query session activity), and their combination, which we refer to as intent.		 Ryen W. White; Paul N. Bennett; Susan T. Dumais;
2010 12 Routing Questions To Appropriate Answerers In Community Question Answering Services
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Highlight: In order to rank the answerers, we propose a framework called Question Routing (QR) which consists of four phases: (1) performance profiling, (2) expertise estimation, (3) availability estimation, and (4) answerer ranking.		 Baichuan Li; Irwin King;
2010 13 Fast And Accurate Estimation Of Shortest Paths In Large Graphs
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Highlight: In this paper, we address this problem and present a scalable sketch-based index structure that not only supports estimation of node distances, but also computes corresponding shortest paths themselves.		 Andrey Gubichev; Srikanta Bedathur; Stephan Seufert; Gerhard Weikum;
2010 14 Top-Eye: Top-k Evolving Trajectory Outlier Detection
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Highlight: To that end, in this paper, we provide an evolving trajectory outlier detection method, named TOP-EYE, which continuously computes the outlying score for each trajectory in an accumulating way.		 YONG GE et. al.
2010 15 A Study Of Rumor Control Strategies On Social Networks
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Highlight: In this paper we study and evaluate rumor-like methods for combating the spread of rumors on a social network.		 Rudra M. Tripathy; Amitabha Bagchi; Sameep Mehta;
2009 1 Expected Reciprocal Rank For Graded Relevance
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Highlight: Inspired by the "cascade" user model, we present a new editorial metric for graded relevance which overcomes this difficulty and implicitly discounts documents which are shown below very relevant documents.		 Olivier Chapelle; Donald Metlzer; Ya Zhang; Pierre Grinspan;
2009 2 LoOP: Local Outlier Probabilities
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Highlight: Many outlier detection methods do not merely provide the decision for a single data object being or not being an outlier but give also an outlier score or "outlier factor" signaling "how much" the respective data object is an outlier.		 Hans-Peter Kriegel; Peer Kröger; Erich Schubert; Arthur Zimek;
2009 3 Joint Sentiment/topic Model For Sentiment Analysis
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Highlight: This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text.		 Chenghua Lin; Yulan He;
2009 4 Analyzing And Evaluating Query Reformulation Strategies In Web Search Logs
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Highlight: In this paper, we aim to better understand how web searchers refine queries and form a theoretical foundation for query reformulation.		 Jeff Huang; Efthimis N. Efthimiadis;
2009 5 Stochastic Gradient Boosted Distributed Decision Trees
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Highlight: In this work, we present two different distributed methods that generates exact stochastic GBDT models, the first is a MapReduce implementation and the second utilizes MPI on the Hadoop grid environment.		 Jerry Ye; Jyh-Herng Chow; Jiang Chen; Zhaohui Zheng;
2009 6 Fast Shortest Path Distance Estimation In Large Networks
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Highlight: In this paper we study approximate landmark-based methods for point-to-point distance estimation in very large networks.		 Michalis Potamias; Francesco Bonchi; Carlos Castillo; Aristides Gionis;
2009 7 Personalized Social Search Based On The User’s Social Network
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Highlight: In the on-line study we analyze the feedback of 240 employees exposed to the alternative personalization approaches.		 DAVID CARMEL et. al.
2009 8 Group-by Skyline Query Processing In Relational Engines
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Highlight: In this paper, we present a comprehensive study on processing group-by skyline queries in the context of relational engines.		 Ming-Hay Luk; Man Lung Yiu; Eric Lo;
2009 9 Exploiting Internal And External Semantics For The Clustering Of Short Texts Using World Knowledge
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Highlight: In this paper, we propose a novel framework to improve the performance of short texts clustering by exploiting the internal semantics from original text and external concepts from world knowledge.		 Xia Hu; Nan Sun; Chao Zhang; Tat-Seng Chua;
2009 10 Event Detection From Flickr Data Through Wavelet-based Spatial Analysis
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Highlight: Our focus in this paper is to detect events from photos on Flickr, an Internet image community website.		 Ling Chen; Abhishek Roy;
2009 11 Scalable Learning Of Collective Behavior Based On Sparse Social Dimensions
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Highlight: In this work, we aim to learn to predict collective behavior in social media.		 Lei Tang; Huan Liu;
2009 12 Improvements That Don’t Add Up: Ad-hoc Retrieval Results Since 1998
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Highlight: In this paper, we analyze results achieved on the TREC Ad-Hoc, Web, Terabyte, and Robust collections as reported in SIGIR (1998–2008) and CIKM (2004–2008).		 Timothy G. Armstrong; Alistair Moffat; William Webber; Justin Zobel;
2009 13 The Effect Of Negation On Sentiment Analysis And Retrieval Effectiveness
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Highlight: We investigate the problem of determining the polarity of sentiments when one or more occurrences of a negation term such as "not" appear in a sentence.		 Lifeng Jia; Clement Yu; Weiyi Meng;
2009 14 P-Rank: A Comprehensive Structural Similarity Measure Over Information Networks
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Highlight: In this paper, we propose a new similarity measure, P-Rank (Penetrating Rank), toward effectively computing the structural similarities of entities in real information networks.		 Peixiang Zhao; Jiawei Han; Yizhou Sun;
2009 15 A Comparative Study Of Methods For Estimating Query Language Models With Pseudo Feedback
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Highlight: We systematically compare five representative state-of-the-art methods for estimating query language models with pseudo feedback in ad hoc information retrieval, including two variants of the relevance language model, two variants of the mixture feedback model, and the divergence minimization estimation method.		 Yuanhua Lv; ChengXiang Zhai;
2008 1 SoRec: Social Recommendation Using Probabilistic Matrix Factorization
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Highlight: Following the intuition that a person’s social network will affect personal behaviors on the Web, this paper proposes a factor analysis approach based on probabilistic matrix factorization to solve the data sparsity and poor prediction accuracy problems by employing both users’ social network information and rating records.		 Hao Ma; Haixuan Yang; Michael R. Lyu; Irwin King;
2008 2 Learning To Link With Wikipedia
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Highlight: This paper describes how to automatically cross-reference documents with Wikipedia: the largest knowledge base ever known.		 David Milne; Ian H. Witten;
2008 3 Beyond The Session Timeout: Automatic Hierarchical Segmentation Of Search Topics In Query Logs
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Highlight: In this work we study real sessions manually labeled into hierarchical tasks, and show that timeouts, whatever their length, are of limited utility in identifying task boundaries, achieving a maximum precision of only 70%.		 Rosie Jones; Kristina Lisa Klinkner;
2008 4 Query Suggestion Using Hitting Time
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Highlight: In this work, we propose a novel query suggestion algorithm based on ranking queries with the hitting time on a large scale bipartite graph.		 Qiaozhu Mei; Dengyong Zhou; Kenneth Church;
2008 5 Can All Tags Be Used For Search?
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Highlight: This paper is the first to present an in-depth study of tagging behavior for very different kinds of resources and systems – Web pages (Del.icio.us), music (Last.fm), and images (Flickr) – and compares the results with anchor text characteristics.		 Kerstin Bischoff; Claudiu S. Firan; Wolfgang Nejdl; Raluca Paiu;
2008 6 The Query-flow Graph: Model And Applications
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Highlight: In this paper we introduce the query-flow graph, a graph representation of the interesting knowledge about latent querying behavior.		 PAOLO BOLDI et. al.
2008 7 How Does Clickthrough Data Reflect Retrieval Quality?
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Highlight: We present a sequence of studies investigating this relationship for an operational search engine on the arXiv.org e-print archive.		 Filip Radlinski; Madhu Kurup; Thorsten Joachims;
2008 8 Mining Social Networks Using Heat Diffusion Processes For Marketing Candidates Selection
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Highlight: We propose to model social network marketing using Heat Diffusion Processes.		 Hao Ma; Haixuan Yang; Michael R. Lyu; Irwin King;
2008 9 Proactive Learning: Cost-sensitive Active Learning With Multiple Imperfect Oracles
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Abstract: Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the …		 Pinar Donmez; Jaime G. Carbonell;
2008 10 Understanding The Relationship Between Searchers’ Queries And Information Goals
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Highlight: We describe results from Web search log studies aimed at elucidating user behaviors associated with queries and destination URLs that appear with different frequencies.		 Doug Downey; Susan Dumais; Dan Liebling; Eric Horvitz;
2008 11 Discovering Leaders From Community Actions
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Highlight: We introduce a novel frequent pattern mining approach to discover leaders and tribes in social networks.		 Amit Goyal; Francesco Bonchi; Laks V.S. Lakshmanan;
2008 12 Link Privacy In Social Networks
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Highlight: We consider a privacy threat to a social network in which the goal of an attacker is to obtain knowledge of a significant fraction of the links in the network.		 Aleksandra Korolova; Rajeev Motwani; Shubha U. Nabar; Ying Xu;
2008 13 BNS Feature Scaling: An Improved Representation Over Tf-idf For Svm Text Classification
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Abstract: In the realm of machine learning for text classification, TF-IDF is the most widely used representation for real-valued feature vectors. However, IDF is oblivious to the training …		 George Forman;
2008 14 Mining Term Association Patterns From Search Logs For Effective Query Reformulation
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Highlight: In this paper, we propose to mine search engine logs for patterns at the level of terms through analyzing the relations of terms inside a query.		 Xuanhui Wang; ChengXiang Zhai;
2008 15 Modeling Hidden Topics On Document Manifold
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Highlight: In this paper, we consider the problem of topic modeling on intrinsic document manifold.		 Deng Cai; Qiaozhu Mei; Jiawei Han; Chengxiang Zhai;
2007 1 Wikify!: Linking Documents To Encyclopedic Knowledge
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Highlight: This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks.		 Rada Mihalcea; Andras Csomai;
2007 2 A Comparison Of Statistical Significance Tests For Information Retrieval Evaluation
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Highlight: For each of these five tests, we took the ad-hoc retrieval runs submitted to TRECs 3 and 5-8, and for each pair of runs, we measured the statistical significance of the difference in their mean average precision.		 Mark D. Smucker; James Allan; Ben Carterette;
2007 3 Autonomously Semantifying Wikipedia
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Highlight: This paper argues that autonomously "Semantifying Wikipedia" is the best way to solve the problem.		 Fei Wu; Daniel S. Weld;
2007 4 Learning On The Border: Active Learning In Imbalanced Data Classification
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Highlight: In this paper, we demonstrate that active learning is capable of solving the class imbalance problem by providing the learner more balanced classes.		 Seyda Ertekin; Jian Huang; Leon Bottou; Lee Giles;
2007 5 Web Search Personalization With Ontological User Profiles
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Highlight: We present an approach to personalized search that involves building models of user context as ontological profiles by assigning implicitly derived interest scores to existing concepts in a domain ontology.		 Ahu Sieg; Bamshad Mobasher; Robin Burke;
2007 6 Discovering Authorities In Question Answer Communities By Using Link Analysis
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Highlight: We present an analysis of the link structure of a general-purpose question answering community to discover authoritative users, and promising experimental results over a dataset of more than 3 million answers from a popular community QA site.		 Pawel Jurczyk; Eugene Agichtein;
2007 7 Measuring Article Quality In Wikipedia: Models And Evaluation
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Highlight: In this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of Wikipedia.		 Meiqun Hu; Ee-Peng Lim; Aixin Sun; Hady Wirawan Lauw; Ba-Quy Vuong;
2007 8 Detecting Distance-based Outliers In Streams Of Data
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Highlight: In this work a method for detecting distance-based outliers in data streams is presented.		 Fabrizio Angiulli; Fabio Fassetti;
2007 9 Identifying Opinion Leaders In The Blogosphere
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Highlight: In this paper, we propose a novel algorithm called InfluenceRank to identify opinion leaders in the blogosphere.		 Xiaodan Song; Yun Chi; Koji Hino; Belle Tseng;
2007 10 Effective Keyword Search For Valuable Lcas Over Xml Documents
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Highlight: In this paper, we study the problem of effective keyword search over XML documents.		 Guoliang Li; Jianhua Feng; Jianyong Wang; Lizhu Zhou;
2007 11 A Knowledge-based Search Engine Powered By Wikipedia
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Highlight: This paper describes Koru, a new search interface that offers effective domain-independent knowledge-based information retrieval.		 David N. Milne; Ian H. Witten; David M. Nichols;
2007 12 Opinion Retrieval From Blogs
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Highlight: In this paper, we describe an opinion retrieval algorithm.		 Wei Zhang; Clement Yu; Weiyi Meng;
2007 13 Proximity-based Document Representation For Named Entity Retrieval
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Highlight: The main contribution of this work is an effective formal method for explicitly modeling the dependency between the named entities and terms which appear in a document.		 Desislava Petkova; W. Bruce Croft;
2007 14 Spam Filtering For Short Messages
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Highlight: We consider the problem of content-based spam filtering for short text messages that arise in three contexts: mobile (SMS) communication, blog comments, and email summary information such as might be displayed by a low-bandwidth client.		 Gordon V. Cormack; José María Gómez Hidalgo; Enrique Puertas Sánz;
2007 15 Discovering Interesting Usage Patterns In Text Collections: Integrating Text Mining With Visualization
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Highlight: This paper addresses the problem of making text mining results more comprehensible to humanities scholars, journalists, intelligence analysts, and other researchers, in order to support the analysis of text collections.		 ANTHONY DON et. al.
2006 1 Movie Review Mining And Summarization
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Highlight: In this paper, we focus on a specific domain – movie review.		 Li Zhuang; Feng Jing; Xiao-Yan Zhu;
2006 2 Estimating Average Precision With Incomplete And Imperfect Judgments
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Highlight: In this work, we propose three evaluation measures that (1) are approximations to average precision even when the relevance judgments are incomplete and (2) are more robust to incomplete or imperfect relevance judgments than bpref.		 Emine Yilmaz; Javed A. Aslam;
2006 3 Voting For Candidates: Adapting Data Fusion Techniques For An Expert Search Task
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Highlight: In this paper, we propose a novel approach for predicting and ranking candidate expertise with respect to a query.		 Craig Macdonald; Iadh Ounis;
2006 4 Utility Scoring Of Product Reviews
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Highlight: We identify a new task in the ongoing research in text sentiment analysis: predicting utility of product reviews, which is orthogonal to polarity classification and opinion extraction.		 Zhu Zhang; Balaji Varadarajan;
2006 5 Cache-oblivious Nested-loop Joins
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Highlight: We propose to adapt the newly emerged cache-oblivious model to relational query processing.		 Bingsheng He; Qiong Luo;
2006 6 On The Structural Properties Of Massive Telecom Call Graphs: Findings And Implications
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Highlight: Based on our analysis, we introduce the Treasure-Hunt model to describe the shape of mobile call graphs.		 AMIT A. NANAVATI et. al.
2006 7 Ranking Robustness: A Novel Framework To Predict Query Performance
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Highlight: In this paper, we introduce the notion of ranking robustness, which refers to a property of a ranked list of documents that indicates how stable the ranking is in the presence of uncertainty in the ranked documents.		 Yun Zhou; W. Bruce Croft;
2006 8 A Data Stream Language And System Designed For Power And Extensibility
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Highlight: ESL supports physical and logical windows (with optional slides and tumbles) on both built-in aggregates and UDAs, using a simple framework that applies uniformly to both aggregate functions written in an external procedural languages and those natively written in ESL.		 Yijian Bai; Hetal Thakkar; Haixun Wang; Chang Luo; Carlo Zaniolo;
2006 9 Incremental Hierarchical Clustering Of Text Documents
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Highlight: We discuss why, in the current form, these algorithms are not suitable for text clustering and propose an alternative formulation that includes changes to the underlying distributional assumption of the algorithm in order to conform with the data.		 Nachiketa Sahoo; Jamie Callan; Ramayya Krishnan; George Duncan; Rema Padman;
2006 10 SaLSa: Computing The Skyline Without Scanning The Whole Sky
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Highlight: In this paper we introduce SaLSa (Sort and Limit Skyline algorithm), which exploits the sorting machinery of a relational engine to order tuples so that only a subset of them needs to be examined for computing the skyline result.		 Ilaria Bartolini; Paolo Ciaccia; Marco Patella;
2006 11 A Study On The Effects Of Personalization And Task Information On Implicit Feedback Performance
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Highlight: In this paper we describe a study on the effect on retrieval performance of using additional information about the user and their search tasks when developing IRF algorithms.		 Ryen W. White; Diane Kelly;
2006 12 Optimisation Methods For Ranking Functions With Multiple Parameters
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Highlight: We build on recent advances in alternative differentiable pairwise cost functions, and show that these techniques can be successfully applied to tuning the parameters of an existing family of IR scoring functions (BM25), in the sense that we cannot do better using sensible search heuristics that directly optimize the rank-based cost function NDCG.		 Michael Taylor; Hugo Zaragoza; Nick Craswell; Stephen Robertson; Chris Burges;
2006 13 An Integer Programming Approach For Frequent Itemset Hiding
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Highlight: In this paper, we investigate the problem of securing sensitive knowledge from being exposed in patterns extracted during association rule mining.		 Aris Gkoulalas-Divanis; Vassilios S. Verykios;
2006 14 On GMAP: And Other Transformations
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Highlight: This paper discusses the status of this measure and how it should be understood.		 Stephen Robertson;
2006 15 A Fast And Robust Method For Web Page Template Detection And Removal
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Highlight: In this paper we present a new method that efficiently and accurately removes templates found in collections of web pages.		 KARANE VIEIRA et. al.
2005 1 Using Appraisal Groups For Sentiment Analysis
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Highlight: We present a new method for sentiment classification based on extracting and analyzing appraisal groups such as “very good” or “not terribly funny”.		 Casey Whitelaw; Navendu Garg; Shlomo Argamon;
2005 2 Implicit User Modeling For Personalized Search
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Highlight: In this paper, we study how to infer a user’s interest from the user’s search context and use the inferred implicit user model for personalized search.		 Xuehua Shen; Bin Tan; ChengXiang Zhai;
2005 3 Time Weight Collaborative Filtering
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Highlight: In this paper, we present a novel algorithm to compute the time weights for different items in a manner that will assign a decreasing weight to old data.		 Yi Ding; Xue Li;
2005 4 Collective Multi-label Classification
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Highlight: This paper explores multi-label conditional random field (CRF)classification models that directly parameterize label co-occurrences in multi-label classification.		 Nadia Ghamrawi; Andrew McCallum;
2005 5 Finding Similar Questions In Large Question And Answer Archives
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Highlight: In this paper, we discuss methods for question retrieval that are based on using the similarity between answers in the archive to estimate probabilities for a translation-based retrieval model.		 Jiwoon Jeon; W. Bruce Croft; Joon Ho Lee;
2005 6 Determining The Semantic Orientation Of Terms Through Gloss Classification
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Highlight: In this paper we present a new method for determining the orientation of subjective terms.		 Andrea Esuli; Fabrizio Sebastiani;
2005 7 Domain-specific Keyphrase Extraction
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Highlight: This paper describes a Keyphrase Identification Program (KIP), which extracts document keyphrases by using prior positive samples of human identified domain keyphrases to assign weights to the candidate keyphrases.		 Yi-fang Brook Wu; Quanzhi Li; Razvan Stefan Bot; Xin Chen;
2005 8 Hybrid Index Structures For Location-based Web Search
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Highlight: In this paper, we propose to use a hybrid index structure, which integrates inverted files and R*-trees, to handle both textual and location aware queries.		 Yinghua Zhou; Xing Xie; Chuang Wang; Yuchang Gong; Wei-Ying Ma;
2005 9 Fast Webpage Classification Using URL Features
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Highlight: We demonstrate the usefulness of the uniform resource locator (URL) alone in performing web page classification.		 Min-Yen Kan; Hoang Oanh Nguyen Thi;
2005 10 ViPER: Augmenting Automatic Information Extraction With Visual Perceptions
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Highlight: In this paper we address the problem of unsupervised Web data extraction.		 Kai Simon; Georg Lausen;
2005 11 Concept-based Interactive Query Expansion
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Highlight: In this work we propose a novel concept-based query expansion technique, which allows disambiguating queries submitted to search engines.		 Bruno M. Fonseca; Paulo Golgher; Bruno Pôssas; Berthier Ribeiro-Neto; Nivio Ziviani;
2005 12 Finding Experts In Community-based Question-answering Services
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Abstract: No abstract available. …		 Xiaoyong Liu; W. Bruce Croft; Matthew Koll;
2005 13 Similarity Measures For Tracking Information Flow
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Highlight: In this paper, we explore mechanisms for measuring such intermediate kinds of similarity, focusing on the task of identifying where a particular piece of information originated.		 Donald Metzler; Yaniv Bernstein; W. Bruce Croft; Alistair Moffat; Justin Zobel;
2005 14 Query Expansion Using Term Relationships In Language Models For Information Retrieval
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Highlight: In some recent studies, dependence models have been proposed to incorporate term relationships into LM, so that links can be created between words in the same sentence, and term relationships (e.g. synonymy) can be used to expand the document model.		 Jing Bai; Dawei Song; Peter Bruza; Jian-Yun Nie; Guihong Cao;
2005 15 Query Expansion Using Random Walk Models
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Highlight: This is particularly important when trying to predict the probability of relevance of a set of terms given a query, which may involve both lexical and semantic relations between the terms.We describe a Markov chain framework that combines multiple sources of knowledge on term associations.		 Kevyn Collins-Thompson; Jamie Callan;
2004 1 Swoogle: A Search And Metadata Engine For The Semantic Web
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Highlight: Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents.		 LI DING et. al.
2004 2 Simple BM25 Extension To Multiple Weighted Fields
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Highlight: This paper describes a simple way of adapting the BM25 ranking formula to deal with structured documents.		 Stephen Robertson; Hugo Zaragoza; Michael Taylor;
2004 3 Hierarchical Document Categorization With Support Vector Machines
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Highlight: In this paper, we propose a novel hierarchical classification method that generalizes Support Vector Machine learning and that is based on discriminant functions that are structured in a way that mirrors the class hierarchy.		 Lijuan Cai; Thomas Hofmann;
2004 4 Optimizing Web Search Using Web Click-through Data
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Highlight: In this paper, we propose a novel iterative reinforced algorithm to utilize the user click-through data to improve search performance.		 GUI-RONG XUE et. al.
2004 5 Event Threading Within News Topics
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Highlight: In this work, we attempt to capture the rich structure of events and their dependencies in a news topic through our event models.		 Ramesh Nallapati; Ao Feng; Fuchun Peng; James Allan;
2004 6 Taxonomy-driven Computation Of Product Recommendations
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Highlight: We exploit such taxonomic background knowledge for the computation of personalized recommendations.		 Cai-Nicolas Ziegler; Georg Lausen; Lars Schmidt-Thieme;
2004 7 Stemming And Lemmatization In The Clustering Of Finnish Text Documents
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Highlight: Since Finnish is a highly inflectional and agglutinative language, we hypothesized that lemmatization, involving splitting of the compound words, would be more appropriate normalization approach than the straightforward stemming.		 Tuomo Korenius; Jorma Laurikkala; Kalervo Järvelin; Martti Juhola;
2004 8 Acquisition Of Categorized Named Entities For Web Search
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Highlight: We present a lightly supervised method for acquiring named entities in arbitrary categories.		 Marius Pasca;
2004 9 Efficient Processing Of XML Twig Patterns With Parent Child Edges: A Look-ahead Approach
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Highlight: To overcome this limitation, in this paper, we propose a novel holistic twig join algorithm, namely <i>TwigStackList</i>.		 Jiaheng Lu; Ting Chen; Tok Wang Ling;
2004 10 Scalable Sequential Pattern Mining For Biological Sequences
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Highlight: In this paper, we study how this explosion affects the classic sequential pattern mining, and present a scalable two-phase algorithm to deal with this new explosion.		 Ke Wang; Yabo Xu; Jeffrey Xu Yu;
2004 11 Image Similarity Search With Compact Data Structures
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Highlight: This paper proposes a new similarity search method consisting of three parts.		 Qin Lv; Moses Charikar; Kai Li;
2004 12 A Practical Web-based Approach To Generating Topic Hierarchy For Text Segments
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Highlight: In this paper, we address the problem of generating topic hierarchies for diverse text segments with a general and practical approach that uses the Web as an additional knowledge source.		 Shui-Lung Chuang; Lee-Feng Chien;
2004 13 QFilter: Fine-grained Run-time XML Access Control Via NFA-based Query Rewriting
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Highlight: In this paper, we take a different approach that assumes no security support from underlying XML databases and examine three alternative fine-grained XML access control solutions, namely <i>primitive, pre-processing</i> and <i>post-processing</i> approaches.		 Bo Luo; Dongwon Lee; Wang-Chien Lee; Peng Liu;
2004 14 Computing Consistent Query Answers Using Conflict Hypergraphs
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Highlight: We present here a practical framework for computing consistent query answers for large, possibly inconsistent relational databases.		 Jan Chomicki; Jerzy Marcinkowski; Slawomir Staworko;
2004 15 Feature Selection With Conditional Mutual Information Maximin In Text Categorization
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Highlight: In this paper, we propose a novel feature selection method for text categorization called <i>conditional mutual information maximin</i> (CMIM).		 Gang Wang; Frederick H. Lochovsky;
2003 1 The Link Prediction Problem For Social Networks
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Highlight: We formalize this question as the link prediction problem, and develop approaches to link prediction based on measures the "proximity" of nodes in a network.		 David Liben-Nowell; Jon Kleinberg;
2003 2 Efficient Query Evaluation Using A Two-level Retrieval Process
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Highlight: We present an efficient query evaluation method based on a two level approach: at the first level, our method iterates in parallel over query term postings and identifies candidate documents using an approximate evaluation taking into account only partial information on term occurrences and no query independent factors; at the second level, promising candidates are fully evaluated and their exact scores are computed.		 Andrei Z. Broder; David Carmel; Michael Herscovici; Aya Soffer; Jason Zien;
2003 3 Expertise Identification Using Email Communications
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Highlight: To find answers to these questions, two algorithms for determining expertise from email were compared: a content-based approach that takes account only of email text, and a graph-based ranking algorithm (HITS) that takes account both of text and communication patterns.		 Christopher S. Campbell; Paul P. Maglio; Alex Cozzi; Byron Dom;
2003 4 Time-based Language Models
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Highlight: We propose a time-based language model approach to retrieval for these queries.		 Xiaoyan Li; W. Bruce Croft;
2003 5 Content-based Retrieval In Hybrid Peer-to-peer Networks
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Highlight: In this paper, we study the application of content-based resource selection and document retrieval to hybrid peer-to-peer networks.		 Jie Lu; Jamie Callan;
2003 6 Ontologies For Semantically Interoperable Systems
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Highlight: In this paper, we discuss the use of ontologies for semantic interoperability and integration.		 Leo Obrst;
2003 7 Categorizing Web Queries According To Geographical Locality
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Highlight: In this paper, we address this problem by first defining how to categorize queries according to their (often implicit) geographical locality.		 Luis Gravano; Vasileios Hatzivassiloglou; Richard Lichtenstein;
2003 8 Statistical Transliteration For English-arabic Cross Language Information Retrieval
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Highlight: In the present study, we present a simple statistical technique to train an English to Arabic transliteration model from pairs of names.		 Nasreen AbdulJaleel; Leah S. Larkey;
2003 9 Dynamically Maintaining Frequent Items Over A Data Stream
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Highlight: In this paper, we propose a new novel algorithm, called hCount, which can handle both insertion and deletion of items with a much less memory space than the best reported algorithm.		 Cheqing Jin; Weining Qian; Chaofeng Sha; Jeffrey X. Yu; Aoying Zhou;
2003 10 Query Expansion Using Associated Queries
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Highlight: We propose a new method of obtaining expansion terms, based on selecting terms from past user queries that are associated with documents in the collection.		 Bodo Billerbeck; Falk Scholer; Hugh E. Williams; Justin Zobel;
2003 11 XML Parsing: A Threat To Database Performance
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Highlight: We report real-word database applications where XML parsing performance is a key obstacle to a successful XML deployment.		 Matthias Nicola; Jasmi John;
2003 12 High Dimensional Reverse Nearest Neighbor Queries
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Highlight: In this paper, we propose an approximate solution to answer RNN queries in high dimensions.		 Amit Singh; Hakan Ferhatosmanoglu; Ali Şaman Tosun;
2003 13 Visualization Of Communication Patterns In Collaborative Innovation Networks – Analysis Of Some W3C Working Groups
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Highlight: Collaborative Innovation Networks (COINs) are groups of self-motivated individuals from various parts of an organization or from multiple organizations, empowered by the Internet, who work together on a new idea, driven by a common vision.		 Peter A. Gloor; Rob Laubacher; Scott B. C. Dynes; Yan Zhao;
2003 14 Question Answering From The Web Using Knowledge Annotation And Knowledge Mining Techniques
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Highlight: We present a strategy for answering fact-based natural language questions that is guided by a characterization of real-world user queries.		 Jimmy Lin; Boris Katz;
2003 15 Combining Link-based And Content-based Methods For Web Document Classification
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Highlight: This work provides an important insight on which measures derived from links are more appropriate to compare Web documents and how these measures can be combined with content-based algorithms to improve the effectiveness of Web classification.		 P&AACUTE;VEL CALADO et. al.
2002 1 Evaluation Of Hierarchical Clustering Algorithms For Document Datasets
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Highlight: We present a new class of clustering algorithms called constrained agglomerative algorithms that combine the features of both partitional and agglomerative algorithms.		 Ying Zhao; George Karypis;
2002 2 Alternatives To The K-means Algorithm That Find Better Clusterings
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Highlight: We describe each algorithm in a unified framework that introduces separate cluster membership and data weight functions.		 Greg Hamerly; Charles Elkan;
2002 3 A Local Search Mechanism For Peer-to-peer Networks
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Highlight: We propose two mechanisms for information retrieval in pure peer-to-peer networks.		 Vana Kalogeraki; Dimitrios Gunopulos; D. Zeinalipour-Yazti;
2002 4 COOLCAT: An Entropy-based Algorithm For Categorical Clustering
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Highlight: In this paper we explore the connection between clustering categorical data and entropy: clusters of similar poi lower entropy than those of dissimilar ones.		 Daniel Barbará; Yi Li; Julia Couto;
2002 5 High-performing Feature Selection For Text Classification
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Highlight: We found that feature selection methods based on chi2 statistics consistently outperformed those based on other criteria (including information gain) for all four classifiers and both data collections, and that a further increase in performance was obtained by combining uncorrelated and high-performing feature selection methods.The results we obtained using only 3% of the available features are among the best reported, including results obtained with the full feature set.		 Monica Rogati; Yiming Yang;
2002 6 A Compact And Efficient Image Retrieval Approach Based On Border/interior Pixel Classification
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Highlight: This paper presents \bic (Border/Interior pixel Classification), a compact and efficient CBIR approach suitable for broad image domains.		 Renato O. Stehling; Mario A. Nascimento; Alexandre X. Falcão;
2002 7 Personalized Web Search By Mapping User Queries To Categories
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Highlight: We propose a novel technique to map a user query to a set of categories, which represent the user’s search intention.		 Fang Liu; Clement Yu; Weiyi Meng;
2002 8 Condorcet Fusion For Improved Retrieval
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Highlight: We present a new algorithm for improving retrieval results by combining document ranking functions: Condorcet-fuse.		 Mark Montague; Javed A. Aslam;
2002 9 Mining Sequential Patterns With Constraints In Large Databases
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Highlight: In this paper, we investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit our missions well.		 Jian Pei; Jiawei Han; Wei Wang;
2002 10 Information Retrieval On The Semantic Web
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Highlight: We describe an approach to retrieval of documents that contain of both free text and semantically enriched markup.		 Urvi Shah; Tim Finin; Anupam Joshi; R. Scott Cost; James Matfield;
2002 11 XClust: Clustering XML Schemas For Effective Integration
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Highlight: We introduce XClust, a novel integration strategy that involves the clustering of DTDs.		 Mong Li Lee; Liang Huai Yang; Wynne Hsu; Xia Yang;
2002 12 Passage Retrieval Based On Language Models
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Highlight: Previous research has shown that passage-level evidence can bring added benefits to document retrieval when documents are long or span different subject areas.		 Xiaoyong Liu; W. Bruce Croft;
2002 13 On Arabic Search: Improving The Retrieval Effectiveness Via A Light Stemming Approach
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Highlight: We present two stemming algorithms for Arabic information retrieval systems.		 Mohammed Aljlayl; Ophir Frieder;
2002 14 A Language Modeling Framework For Resource Selection And Results Merging
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Highlight: Statistical language models have been proposed recently for several information retrieval tasks, including the resource selection task in distributed information retrieval.		 Luo Si; Rong Jin; Jamie Callan; Paul Ogilvie;
2002 15 Topic-based Document Segmentation With Probabilistic Latent Semantic Analysis
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Highlight: This paper presents a new method for topic-based document segmentation, i.e., the identification of boundaries between parts of a document that bear on different topics.		 Thorsten Brants; Francine Chen; Ioannis Tsochantaridis;
2001 1 Managing Trust In A Peer-2-peer Information System
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Highlight: In this paper we present an approach that addresses the problem of reputation-based trust management at both the data management and the semantic level.		 Karl Aberer; Zoran Despotovic;
2001 2 Model-based Feedback In The Language Modeling Approach To Information Retrieval
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Highlight: In this paper, we present a more principled approach to feedback in the language modeling approach.		 Chengxiang Zhai; John Lafferty;
2001 3 Evaluation Of Item-Based Top-N Recommendation Algorithms
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Highlight: Our experimental evaluation on five different datasets show that the proposed item-based algorithms are up to 28 times faster than the traditional user-neighborhood based recommender systems and provide recommendations whose quality is up to 27% better.		 George Karypis;
2001 4 Bipartite Graph Partitioning And Data Clustering
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Highlight: In this paper, we propose a new data clustering method based on partitioning the underlying bipartite graph.		 Hongyuan Zha; Xiaofeng He; Chris Ding; Horst Simon; Ming Gu;
2001 5 A Statistical Model For Scientific Readability
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Highlight: In this paper, we present a new method of using statistical models to estimate readability [1].		 Luo Si; Jamie Callan;
2001 6 Multi-dimensional Sequential Pattern Mining
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Highlight: It is interesting and useful to mine sequential patterns associated with multi-dimensional information.In this paper, we propose the theme of multi-dimensional sequential pattern mining, which integrates the multidimensional analysis and sequential data mining.		 HELEN PINTO et. al.
2001 7 Evaluating Document Clustering For Interactive Information Retrieval
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Highlight: We consider the problem of organizing and browsing the top ranked portion of the documents returned by an information retrieval system.		 Anton Leuski;
2001 8 Keeping Found Things Found On The Web
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Highlight: This paper describes the results of an observational study into the methods people use to manage web information for re-use.		 William Jones; Harry Bruce; Susan Dumais;
2001 9 Sliding-window Filtering: An Efficient Algorithm For Incremental Mining
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Highlight: We explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules.		 Chang-Hung Lee; Cheng-Ru Lin; Ming-Syan Chen;
2001 10 Relevance Score Normalization For Metasearch
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Highlight: In this paper, we show that the techniques used for normalizing relevance scores and estimating the relevance scores of unretrieved documents can have a significant effect on the overall performance of metasearch.		 Mark Montague; Javed A. Aslam;
2001 11 Using LSI For Text Classification In The Presence Of Background Text
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Highlight: This paper presents work that uses Latent Semantic Indexing (LSI) for text classification.		 Sarah Zelikovitz; Haym Hirsh;
2001 12 A Music Recommendation System Based On Music Data Grouping And User Interests
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Highlight: In this paper, we design the Music Recommendation System (MRS) to provide a personalized service of music recommendation.		 Hung-Chen Chen; Arbee L. P. Chen;
2001 13 Mining The Web To Create Minority Language Corpora
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Highlight: We describe CorpusBuilder, an approach for automatically generating Web-search queries for collecting documents in a minority language.		 Rayid Ghani; Rosie Jones; Dunja Mladenić;
2001 14 Summarization As Feature Selection For Text Categorization
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Highlight: We address the problem of evaluating the effectiveness of summarization techniques for the task of document categorization.		 Aleksander Kolcz; Vidya Prabakarmurthi; Jugal Kalita;
2001 15 Rapid Association Rule Mining
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Highlight: In this paper, we propose an innovative algorithm called Rapid Association Rule Mining (RARM) to once again break this speed barrier.		 Amitabha Das; Wee-Keong Ng; Yew-Kwong Woon;
2000 1 Analyzing The Effectiveness And Applicability Of Co-training
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Abstract: No abstract available. …		 Kamal Nigam; Rayid Ghani;
2000 2 Sequence Mining In Categorical Domains: Incorporating Constraints
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Abstract: No abstract available. …		 Mohammed J. Zaki;
2000 3 A Comparison Of DFT And DWT Based Similarity Search In Time-series Databases
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Abstract: No abstract available. …		 Yi-Leh Wu; Divyakant Agrawal; Amr El Abbadi;
2000 4 Clustering Through Decision Tree Construction
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Abstract: No abstract available. …		 Bing Liu; Yiyuan Xia; Philip S. Yu;
2000 5 First Story Detection In TDT Is Hard
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Abstract: No abstract available. …		 James Allan; Victor Lavrenko; Hubert Jin;
2000 6 Language Models For Financial News Recommendation
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Abstract: No abstract available. …		 VICTOR LAVRENKO et. al.
2000 7 WebCQ-detecting And Delivering Information Changes On The Web
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Abstract: No abstract available. …		 Ling Liu; Calton Pu; Wei Tang;
2000 8 Personal Ontologies For Web Navigation
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Abstract: No abstract available. …		 Jason Chaffee; Susan Gauch;
2000 9 Automatically Summarising Web Sites: Is There A Way Around It?
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Abstract: No abstract available. …		 Einat Amitay; Cécile Paris;
2000 10 Vector Approximation Based Indexing For Non-uniform High Dimensional Data Sets
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Abstract: No abstract available. …		 Hakan Ferhatosmanoglu; Ertem Tuncel; Divyakant Agrawal; Amr El Abbadi;
2000 11 Collection Selection And Results Merging With Topically Organized U.S. Patents And TREC Data
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Abstract: No abstract available. …		 Leah S. Larkey; Margaret E. Connell; Jamie Callan;
2000 12 Creating And Evaluating Multi-document Sentence Extract Summaries
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Abstract: No abstract available. …		 Jade Goldstein; Vibhu Mittal; Jaime Carbonell; Jamie Callan;
2000 13 Space Efficient Bitmap Indexing
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Abstract: No abstract available. …		 Nick Koudas;
2000 14 Boosting For Document Routing
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Abstract: No abstract available. …		 Raj D. Iyer; David D. Lewis; Robert E. Schapire; Yoram Singer; Amit Singhal;
2000 15 An Improved Boosting Algorithm And Its Application To Text Categorization
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Abstract: No abstract available. …		 Fabrizio Sebastiani; Alessandro Sperduti; Nicola Valdambrini;
1999 1 A General Language Model For Information Retrieval
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Highlight: In this paper, we will present a new language model for information retrieval, which is based on a range of data smoothing techniques, including the Good-Turning estimate, curve-fitting functions, and model combinations.		 Fei Song; W. Bruce Croft;
1999 2 Incremental And Interactive Sequence Mining
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Highlight: In this paper, we propose novel techniques for maintaining sequences in the presence of a) database updates, and b) user interaction (e.g. modifying mining parameters).		 S. Parthasarathy; M. J. Zaki; M. Ogihara; S. Dwarkadas;
1999 3 Clustering Transactions Using Large Items
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Highlight: We present a clustering algorithm based on the new clustering criterion and evaluate its effectiveness.		 Ke Wang; Chu Xu; Bing Liu;
1999 4 Yahoo! As An Ontology: Using Yahoo! Categories To Describe Documents
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Highlight: In the course of investigating this idea, we address the problem of automatic categorization of webpages in the Yahoo! directory.		 Yannis Labrou; Tim Finin;
1999 5 Haystack: Per-user Information Environments
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Highlight: This paper describes the prototype Haystack system.		 Eytan Adar; David Karger; Lynn Andrea Stein;
1999 6 Training A Selection Function For Extraction
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Highlight: In this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence affects the performance of each heuristic.		 Chin-Yew Lin;
1999 7 An Adaptive Algorithm For Learning Changes In User Interests
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Highlight: In this paper, we describe a new scheme to learn dynamic user’s interests in an automated information filtering and gathering system running on the Internet.		 Dwi H. Widyantoro; Thomas R. Ioerger; John Yen;
1999 8 Indexing And Retrieval Of Scientific Literature
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Highlight: This paper discusses the creation of digital libraries of scientific literature on the web, including the efficient location of articles, full-text indexing of the articles, autonomous citation indexing, information extraction, display of query-sensitive summaries and citation context, hubs and authorities computation, similar document detection, user profiling, distributed error correction, graph analysis, and detection of overlapping documents.		 Steve Lawrence; Kurt Bollacker; C. Lee Giles;
1999 9 Architecture Of A Metasearch Engine That Supports User Information Needs
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Highlight: In this paper, we describe a metasearch engine architecture that considers the user’s information need for each decision.		 Eric J. Glover; Steve Lawrence; William P. Birmingham; C. Lee Giles;
1999 10 Extracting Significant Time Varying Features From Text
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Highlight: We propose a simple statistical model for the frequency of occurrence of features in a stream of text.		 Russell Swan; James Allan;
1999 11 Extracting Semi-structured Data Through Examples
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Highlight: In this paper, we describe an innovative approach to extracting semi-structured data from Web sources.		 Berthier Ribeiro-Neto; Alberto H. F. Laender; Altigran S. da Silva;
1999 12 An Automated Approach For Retrieving Hierarchical Data From HTML Tables
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Highlight: In this paper, we propose an automated approach for retrieving hierarchical data from HTML tables.		 Seung-Jin Lim; Yiu-Kai Ng;
1999 13 A Probabilistic Description-oriented Approach For Categorizing Web Documents
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Highlight: Two ways to respond to this challenge are (1) using a representation of the content of web documents that captures these two characteristics and (2) using more effective classifiers.		 Norbert Gövert; Mounia Lalmas; Norbert Fuhr;
1999 14 Text Classification Using ESC-based Stochastic Decision Lists
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Highlight: We propose a new method of text classification using stochastic decision lists.		 Hang Li; Kenji Yamanishi;
1999 15 Semantic Caching Via Query Matching For Web Sources
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Highlight: A polynomial time algorithm based on the proposed query matching technique is presented to find the best matched query in the cache.		 Dongwon Lee; Wesley W. Chu;
1998 1 Inductive Learning Algorithms And Representations For Text Categorization
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Abstract: No abstract available. …		 Susan Dumais; John Platt; David Heckerman; Mehran Sahami;
1998 2 Data Cube Approximation And Histograms Via Wavelets
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Abstract: No abstract available. …		 Jeffrey Scott Vitter; Min Wang; Bala Iyer;
1998 3 Efficient Enumeration Of Frequent Sequences
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Abstract: No abstract available. …		 Mohammed J. Zaki;
1998 4 Ontology-based Extraction And Structuring Of Information From Data-rich Unstructured Documents
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Abstract: No abstract available. …		 David W. Embley; Douglas M. Campbell; Randy D. Smith; Stephen W. Liddle;
1998 5 Efficient Repeating Pattern Finding In Music Databases
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Abstract: No abstract available. …		 Jia-Lien Hsu; Arbee L. P. Chen; C.-C. Liu;
1998 6 MALM: A Framework For Mining Sequence Database At Multiple Abstraction Levels
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Abstract: No abstract available. …		 Chung-Sheng Li; Philip S. Yu; Vittorio Castelli;
1998 7 Supporting Fast Search In Time Series For Movement Patterns In Multiple Scales
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Abstract: No abstract available. …		 Yunyao Qu; Changzhou Wang; X. Sean Wang;
1998 8 SERF: Schema Evolution Through An Extensible, Re-usable And Flexible Framework
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Abstract: No abstract available. …		 Kajal T. Claypool; Jing Jin; Elke A. Rundensteiner;
1998 9 A Hierarchical Approach To The Automatic Categorization Of Medical Documents
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Abstract: No abstract available. …		 Luciano R. S. de Lima; Alberto H. F. Laender; Berthier A. Ribeiro-Neto;
1998 10 Accurate User Directed Summarization From Existing Tools
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Abstract: No abstract available. …		 Mark Sanderson;
1998 11 Modeling Time From A Conceptual Perspective
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Abstract: No abstract available. …		 Stefano Spaccapietra; Christine Parent; Esteban Zimanyi;
1998 12 An Automatic Technique For Detecting Type Conflicts In Database Schemes
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Abstract: No abstract available. …		 Luigi Palopoli; Domenico Saccá; Domenico Ursino;
1998 13 Static And Dynamic Information Organization With Star Clusters
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Abstract: No abstract available. …		 Javed Aslam; Katya Pelekhov; Daniela Rus;
1998 14 Document Classification Using Multiword Features
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Abstract: No abstract available. …		 Ron Papka; James Allan;
1998 15 Clustering And Singular Value Decomposition For Approximate Indexing In High Dimensional Spaces
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Abstract: No abstract available. …		 Alexander Thomasian; Vittorio Castelli; Chung-Sheng Li;
1997 1 Learning Belief Networks From Data: An Information Theory Based Approach
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Abstract: No abstract available. …		 Jie Cheng; David A. Bell; Weiru Liu;
1997 2 Mining Fuzzy Association Rules
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Abstract: No abstract available. …		 Keith C. C. Chan; Wai-Ho Au;
1997 3 Matching And Indexing Sequences Of Different Lengths
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Abstract: No abstract available. …		 Tolga Bozkaya; Nasser Yazdani; Meral Özsoyoğlu;
1997 4 Block Addressing Indices For Approximate Text Retrieval
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Abstract: No abstract available. …		 Ricardo Baeza-Yates; Gonzalo Navarro;
1997 5 Video Keyframe Extraction And Filtering: A Keyframe Is Not A Keyframe To Everyone
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Abstract: No abstract available. …		 Nevenka Dimitrova; Thomas McGee; Herman Elenbaas;
1997 6 Pharos: A Scalable Distributed Architecture For Locating Heterogeneous Information Sources
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Abstract: No abstract available. …		 R. Dolin; D. Agrawal; A. El Abbadi; L. Dillon;
1997 7 Applications Of Approximate Word Matching In Information Retrieval
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Abstract: No abstract available. …		 James C. French; Allison L. Powell; Eric Schulman;
1997 8 Generating Association Rules From Semi-structured Documents Using An Extended Concept Hierarchy
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Abstract: No abstract available. …		 Lisa Singh; Peter Scheuermann; Bin Chen;
1997 9 Improving Relevance Feedback In The Vector Space Model
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Abstract: No abstract available. …		 Carol Lundquist; David A. Grossman; Ophir Frieder;
1997 10 Xmas: An Extensible Main-memory Storage System
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Abstract: No abstract available. …		 Sang Kyun Cha; Jang Ho Park; Byoung Dae Park;
1997 11 A Framework For The Management Of Past Experiences With Time-extended Situations
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Abstract: No abstract available. …		 Michel Jaczynski;
1997 12 A Spatial Match Representation Scheme For Indexing And Querying In Iconic Image Databases
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Abstract: No abstract available. …		 Jae-Woo Chang; Yeon-Jung Kim; Ki-Jin Chang;
1997 13 Mining Association Rules With Adjustable Accuracy
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Abstract: No abstract available. …		 Jong Soo Park; Philip S. Yu; Ming-Syan Chen;
1997 14 A Corpus Analysis Approach For Automatic Query Expansion
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Abstract: No abstract available. …		 Susan Gauch; Jianying Wang;
1996 1 A Data Model For Supporting On-line Analytical Processing
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Abstract: No abstract available. …		 Chang Li; X. Sean Wang;
1996 2 Hierarchical Optimization Of Optimal Path Finding For Transportation Applications
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Abstract: No abstract available. …		 Ning Jing; Yun-Wu Huang; Elke A. Rundensteiner;
1996 3 Efficient Retrieval For Browsing Large Image Databases
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Abstract: No abstract available. …		 Daniel Wu; Ambuj Singh; Divyakant Agrawal; Amr El Abbadi; Terence R. Smith;
1996 4 Effective Graph Clustering For Path Queries In Digital Map Databases
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Abstract: No abstract available. …		 Yun-Wu Huang; Ning Jing; Elke A. Rundensteiner;
1996 5 The Personal Electronic Program Guide—towards The Pre-selection Of Individual TV Programs
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Abstract: No abstract available. …		 Michael Ehrmantraut; Theo Härder; Hartmut Wittig; Ralf Steinmetz;
1996 6 Processing Queries For First-few Answers
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Abstract: No abstract available. …		 Roberto J. Bayardo; Daniel P. Miranker;
1996 7 Dynamic Query Optimization On A Distributed Object Management Platform
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Abstract: No abstract available. …		 Fatma Ozcan; Sena Nural; Pinar Koksal; Cem Evrendilek; Asuman Dogac;
1996 8 Object-oriented And Database Concepts For The Design Of Networked Information Retrieval Systems
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Abstract: No abstract available. …		 Norbert Fuhr;
1996 9 Information Agents For Automated Browsing
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Abstract: No abstract available. …		 Chanda Dharap; Martin Freeman;
1996 10 An Object-oriented Approach To Multi-level Association Rule Mining
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Abstract: No abstract available. …		 Scott Fortin; Ling Liu;
1996 11 CROSS-DB: A Feature-extended Multidimensional Data Model For Statistical And Scientific Databases
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Abstract: No abstract available. …		 Wolfgang Lehner; Thomas Ruf; Michael Teschke;
1996 12 Processing OODB Queries By O-Algebra
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Abstract: No abstract available. …		 Jie Lin; Z. Meral Ozsoyoglu;
1996 13 Modeling A Vocabulary In An Object-oriented Database
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Abstract: No abstract available. …		 Li-min Liu; Michael Halper; Huanying Gu; James Geller; Yehoshua Perl;
1996 14 Background For Association Rules And Cost Estimate Of Selected Mining Algorithms
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Abstract: No abstract available. …		 Jia Liang Han; Ashley W. Plank;
1996 15 Indexing Values Of Time Sequences
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Abstract: No abstract available. …		 Ling Lin; Tore Risch; Martin Sköld; Dushan Badal;
1995 1 Research Problems In Data Warehousing
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Abstract: No abstract available. …		 Jennifer Widom;
1995 2 Efficient Parallel Data Mining For Association Rules
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Abstract: No abstract available. …		 Jong Soo Park; Ming-Syan Chen; Philip S. Yu;
1995 3 Using Speculation To Reduce Server Load And Service Time On The WWW
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Abstract: No abstract available. …		 Azer Bestavros;
1995 4 The Role Of Domain Knowledge In Data Mining
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Abstract: No abstract available. …		 Sarabjot S. Anand; David A. Bell; John G. Hughes;
1995 5 Mining Knowledge At Multiple Concept Levels
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Abstract: No abstract available. …		 Jiawei Han;
1995 6 PERF Join: An Alternative To Two-way Semijoin And Bloomjoin
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Abstract: No abstract available. …		 Zhe Li; Kenneth A. Ross;
1995 7 Experimental Evaluation Of Dynamic Data Allocation Strategies In A Distributed Database With Changing Workloads
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Abstract: No abstract available. …		 Anna Brunstrom; Scott T. Leutenegger; Rahul Simha;
1995 8 Automatic Thesaurus Construction Using Bayesian Networks
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Abstract: No abstract available. …		 Young C. Park; Young S. Han; Key-Sun Choi;
1995 9 The Distributed Interoperable Object Model And Its Application To Large-scale Interoperable Database Systems
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Abstract: No abstract available. …		 Ling Liu; Calton Pu;
1995 10 Data Broadcasting Strategies Over Multiple Unreliable Wireless Channels
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Abstract: No abstract available. …		 Hong V. Leong; Antonio Si;
1995 11 A Declarative Formalization Of Knowledge Translation
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Abstract: No abstract available. …		 Saša Buvač; Richard Fikes;
1995 12 An Extensible Knowledge Base Management System For Supporting Rule-based Interoperability Among Heterogeneous Systems
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Abstract: No abstract available. …		 Stanley Y. W. Su; Herman Lam; Javier Arroyo-Figueroa; Tsae-Feng Yu; Zhidong Yang;
1995 13 On The Update Of Term Weights In Dynamic Information Retrieval Systems
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Abstract: No abstract available. …		 Charles L. Viles; James C. French;
1995 14 An Efficient And Reliable Reservation Algorithm For Mobile Transactions
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Abstract: No abstract available. …		 Ahmed Elmagarmid; Jin Jing; Omran Bukhres;
1995 15 Electronic Catalogs: A Technology Overview And Survey Results
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Abstract: No abstract available. …		 Arie Segev; Dadong Wan; Caroline Beam;
1994 1 KQML As An Agent Communication Language
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Highlight: This paper describes the design of and experimentation with the Knowledge Query and Manipulation Language (KQML), a new language and protocol for exchanging information and knowledge.		 Tim Finin; Richard Fritzson; Don McKay; Robin McEntire;
1994 2 Finding Interesting Rules From Large Sets Of Discovered Association Rules
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Highlight: We show how a simple formalism of rule templates makes it possible to easily describe the structure of interesting rules.		 Mika Klemettinen; Heikki Mannila; Pirjo Ronkainen; Hannu Toivonen; A. Inkeri Verkamo;
1994 3 A Semantics Approach For KQML—a General Purpose Communication Language For Software Agents
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Highlight: We investigate the semantics for Knowledge Query Manipulation Language (KQML) and we propose a semantic framework for the language.		 Yannis Labrou; Tim Finin;
1994 4 Building Information Systems For Mobile Environments
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Highlight: In this paper, we report on the development of such a system.		 Evaggelia Pitoura; Bharat Bhargava;
1994 5 The EGG/YOLK Reliability Hierarchy: Semantic Data Integration Using Sorts With Prototypes
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Highlight: We exploit Cui, Cohn and Randell’s Qualitative Spatial Simulation program to create the hierarchy of all possible relations between source and target EGG/YOLK types, ranked by reliability.		 Fritz Lehmann; Anthony G. Cohn;
1994 6 Intelligent Caching: Selecting, Representing, And Reusing Data In An Information Server
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Highlight: This paper presents an approach to caching and addresses the issues of which information to cache, how to describe what has been cached, and how to use the cached information to answer future queries.		 Yigal Arens; Craig A. Knoblock;
1994 7 Semantics-based Information Brokering
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Highlight: We discuss an approach to information brokering in the above environment.		 Vipul Kashyap; Amit Sheth;
1994 8 Context Interchange: Overcoming The Challenges Of Large-scale Interoperable Database Systems In A Dynamic Environment
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Highlight: Research in database interoperability has primarily focused on circumventing schematic and semantic incompatibility arising from autonomy of the underlying databases.		 Cheng Hian Goh; Stuart E. Madnick; Michael D. Siegel;
1994 9 On The Relationship Between Description Logic And Predicate Logic Queries
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Highlight: This paper, aimed at a general audience that includes database researchers, considers the relationship between the expressive power of DLs and that of query languages based on Predicate Calculus.		 Alex Borgida;
1994 10 A Pattern Matching Language For Spatio-temporal Databases
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Highlight: We propose a pattern matching language for spatio-temporal databases.		 Tsz S. Cheng; Shashi K. Gadia;
1994 11 Hashing By Proximity To Process Duplicates In Spatial Databases
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Highlight: A novel approach for duplicate processing based on proximity of spatial objects is presented.		 Walid G. Aref; Hanan Samet;
1994 12 TID Hash Joins
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Abstract: No abstract available. …		 Robert Marek; Erhard Rahm;
1994 13 A Classification Algorithm For Supporting Object-oriented Views
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Highlight: In this paper, we propose a solution to this classification problem that accomplishes the following goals: (1) generate maximally informative, and thus comprehensible, schemas that explicitly model the subclass relationships between base and virtual classes, and (2) support efficient type resolution for shared property functions by supporting upwards inheritance for both base and virtual classes.		 Elke Angelika Rundensteiner;
1994 14 Integrating A Part Relationship Into An Open OODB System Using Metaclasses
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Highlight: In this paper, we examine the problem of integrating such a construct into an OODB system.		 Michael Halper; James Geller; Yehoshua Perl; Wolfgang Klas;
1994 15 Query Expansion Using Domain-adapted, Weighted Thesaurus In An Extended Boolean Model
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Highlight: In this paper, we address there important issues with query expansion using a thesaurus; how to give weights to the terms in expanded queries, how to select additional search terms in the thesaurus, and how to enrich the terms in the manual thesaurus (namely, thesaurus reconstruction).		 Oh-Woog Kwon; Myoung-Cheol Kim; Key-Sun Choi;
1993 1 On Packing R-trees
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Abstract: No abstract available. …		 Ibrahim Kamel; Christos Faloutsos;
1993 2 Word Sense Disambiguation For Free-text Indexing Using A Massive Semantic Network
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Abstract: No abstract available. …		 Michael Sussna;
1993 3 Experiments On Multistrategy Learning By Meta-learning
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Abstract: No abstract available. …		 Philip K. Chan; Salvatore J. Stolfo;
1993 4 Multiple Query Optimization With Depth-First Branch-and-Bound And Dynamic Query Ordering
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Abstract: No abstract available. …		 Ahmet Cosar; Ee-Peng Lim; Jaideep Srivastava;
1993 5 Termination And Confluence Of Rule Execution
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Abstract: No abstract available. …		 Leonie van der Voort; Arno Siebes;
1993 6 Reformulating Query Plans For Multidatabase Systems
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Abstract: No abstract available. …		 Chun-Nan Hsu; Craig A. Knoblock;
1993 7 Data Mining Of Multidimensional Remotely Sensed Images
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Abstract: No abstract available. …		 Robert F. Cromp; William J. Campbell;
1993 8 Towards The Design And Development Of A New Architecture For Geographic Information Systems
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Abstract: No abstract available. …		 Niki Pissinou; Kia Makki; E. K. Park;
1993 9 Translating Description Logics To Information Server Queries
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Abstract: No abstract available. …		 Premkumar T. Devanbu;
1993 10 Query Optimization And Processing In Federated Database Systems
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Abstract: No abstract available. …		 Ee-Peng Lim; Jaideep Srivastava;
1993 11 Automated Cataloging And Analysis Of Sky Survey Image Databases: The SKICAT System
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Abstract: No abstract available. …		 Usama M. Fayyad; Nicholas Weir; S. Djorgovski;
1993 12 Automatic Generation Of Graphical User Interfaces For Interactive Database Applications
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Abstract: No abstract available. …		 Arturo Pizano; Yukari Shirota; Atsushi Iizawa;
1993 13 Adaptive Query Optimization In A Deductive Database System
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Abstract: No abstract available. …		 Marcia A. Derr;
1993 14 An Object-oriented Model For Image Information Representation
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Abstract: No abstract available. …		 James Griffioen; Rajiv Mehrotra; Rajendra Yavatkar;
1993 15 An Information Model For Genome Map Representation And Assembly
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Abstract: No abstract available. …		 A. J. Lee; E. A. Rendensteiner; S. Thomas; S. Lafortune;