Paper Digest: ICDE 2021 Highlights
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TABLE 1: Paper Digest: ICDE 2021 Highlights
| Paper | Author(s) | |
|---|---|---|
| 1 | Profiles of Schema Evolution in Free Open Source Software Projects Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the findings of a large study of the evolution of the schema of 195 Free Open Source Software projects. |
P. Vassiliadis; |
| 2 | CleanML: A Study for Evaluating The Impact of Data Cleaning on ML Classification Tasks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a CleanML study that systematically investigates the impact of data cleaning on ML classification tasks. |
P. Li; X. Rao; J. Blase; Y. Zhang; X. Chu; C. Zhang; |
| 3 | Approximate Order Dependency Discovery Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: (2) We present an efficient approximate OD discovery algorithm that is well suited to the two error measures, with a set of pruning rules and optimization techniques. |
Y. Jin; Z. Tan; W. Zeng; S. Ma; |
| 4 | DBSCOUT: A Density-based Method for Scalable Outlier Detection in Very Large Datasets Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose DBSCOUT, an efficient exact algorithm for outlier detection with a linear complexity that can run in parallel over multiple independent machines, making it a fit for the settings with billions of tuples. |
M. Corain; P. Garza; A. Asudeh; |
| 5 | Bootstrapping Information Extraction Via Conceptualization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a pattern-based extraction framework with three distinguished features: (1) it uses conceptual taxonomies to guide the extraction to reduce semantic drift; (2) it uses the knowledge of existing triples to improve the precision; (3) it integrates all patterns to form a generalized pattern set with quantified confidence measurement. |
J. Liang; S. Feng; C. Xie; Y. Xiao; J. Chen; S. -W. Hwang; |
| 6 | Capturing Semantics for Imputation with Pre-trained Language Models Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this, we propose IPM that captures semantics for Imputation with Pre-trained language Models. |
Y. Mei; S. Song; C. Fang; H. Yang; J. Fang; J. Long; |
| 7 | Manipulating Black-Box Networks for Centrality Promotion Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we explore the following question: given a black-box network whose structure is unknown, is it possible to improve the centrality ranking (rather than the score) of a target node by implementing certain strategies? |
W. Li; M. Gao; F. Wu; W. Rong; J. Wen; L. Qin; |
| 8 | Efficient and Effective Community Search on Large-scale Bipartite Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the significant (a, ?)-community search problem on weighted bipartite graphs. |
K. Wang; W. Zhang; X. Lin; Y. Zhang; L. Qin; Y. Zhang; |
| 9 | Efficient Community Search with Size Constraint Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A hybrid search method is proposed combining the expansion and shrinking strategies, where a score function is used to guide the search order. |
B. Liu; F. Zhang; W. Zhang; X. Lin; Y. Zhang; |
| 10 | Multi-attributed Community Search in Road-social Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this, we introduce a normative community model suitable for multi-criteria decision making, called multi-attributed community (MAC), based on the concepts of k-core and a novel dominance relationship specific to preferences. |
F. Guo; Y. Yuan; G. Wang; X. Zhao; H. Sun; |
| 11 | Peer Learning Through Targeted Dynamic Groups Formation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we initiate a dynamic variant of the problem that, unlike previous works, allows the change of group composition over time while still targeting to maximize the aggregated knowledge level. |
D. Wei; I. Koutis; S. B. Roy; |
| 12 | Efficient 2-Hop Labeling Maintenance in Dynamic Small-World Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we adopt the state-of-the-art Parallel Shortest-distance Labeling (PSL) as the underlying 2-hop labeling construction method, and design algorithms to support efficient update of the index given edge weight change (increase and decrease) in the network. |
M. Zhang; L. Li; W. Hua; X. Zhou; |
| 13 | Differentially Private Publication of Multi-Party Sequential Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In addressing the above challenges, we present DPST, a distributed prediction suffix tree construction solution. |
P. Tang; R. Chen; S. Su; S. Guo; L. Ju; G. Liu; |
| 14 | Secure Dynamic Skyline Queries Using Result Materialization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We show that pre-computing skyline results while minimizing storage overhead is NP-hard, and we provide heuristics that solve the problem more efficiently, while maintaining storage at reasonable levels. |
S. Zeighami; G. Ghinita; C. Shahabi; |
| 15 | P3GM: Private High-Dimensional Data Release Via Privacy Preserving Phased Generative Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the above issue, this paper proposes privacy-preserving phased generative model (P3GM), which is a differentially private generative model for releasing such sensitive data. |
S. Takagi; T. Takahashi; Y. Cao; M. Yoshikawa; |
| 16 | Feature Inference Attack on Model Predictions in Vertical Federated Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents several feature inference attack methods to investigate the potential privacy leakages in the model prediction stage of vertical FL. |
X. Luo; Y. Wu; X. Xiao; B. C. Ooi; |
| 17 | Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap, we propose ThreatRaptor, a system that facilitates threat hunting in computer systems using OSCTI. |
P. Gao; et al. |
| 18 | Twine: An Embedded Trusted Runtime for WebAssembly Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes Twine, a WebAssembly trusted runtime designed to execute unmodified, language-independent applications. |
J. M�n�trey; M. Pasin; P. Felber; V. Schiavoni; |
| 19 | Modeling Citywide Crowd Flows Using Attentive Convolutional LSTM Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to predict citywide crowd flows within a period in the future to give aid to urban management, through modeling spatiotemporal patterns of recent crowd flows. |
C. H. Liu; et al. |
| 20 | A Privacy-Enhanced and Personalized Safe Route Planner with Crowdsourced Data and Computation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel safe route planning problem and develop an efficient solution to ensure the travelers? safety on roads. |
F. T. Islam; T. Hashem; R. Shahriyar; |
| 21 | Coalition-based Task Assignment in Spatial Crowdsourcing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel SC problem, namely Coalition-based Task Assignment (CTA), where the spatial tasks (e.g., house removals, furniture installation) may require more than one workers (forming a coalition) to cooperate in order to maximize the overall rewards of workers. |
Y. Zhao; J. Guo; X. Chen; J. Hao; X. Zhou; K. Zheng; |
| 22 | Crowdsensing Data Trading Based on Combinatorial Multi-Armed Bandit and Stackelberg Game Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a data trading mechanism based on Combinatorial Multi-Armed Bandit and three-stage Hierarchical Stackelberg game, called CMAB-HS, to tackle the problem of quality unknown seller selection and incentive strategy design. |
B. An; M. Xiao; A. Liu; X. Xie; X. Zhou; |
| 23 | Fairness-aware Task Assignment in Spatial Crowdsourcing: Game-Theoretic Approaches Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we aim to minimize the payoff difference among workers while maximizing the average worker payoff. |
Y. Zhao; K. Zheng; J. Guo; B. Yang; T. B. Pedersen; C. S. Jensen; |
| 24 | A Human-in-the-loop Approach to Social Behavioral Targeting Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a two-pronged approach to behavioral targeting that effectively addresses the above difficulties. |
J. Yang; et al. |
| 25 | CrowdRL: An End-to-End Reinforcement Learning Framework for Data Labelling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In other words, they ignore the correlation between them (the labelled data may have noise caused by humans with biases, and the model trained by the noisy labels may bring additional biases), and thus lead to poor inference results.To address these limitations, in this paper, we propose CrowdRL, an end-to-end reinforcement learning (RL) based framework for data labelling. |
K. Li; G. Li; Y. Wang; Y. Huang; Z. Liu; Z. Wu; |
| 26 | Rebuilding City-Wide Traffic Origin Destination from Road Speed Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new method that models the complex process via separate modules and takes auxiliary data to eliminate infeasible solutions. |
G. Zheng; C. Liu; H. Wei; C. Chen; Z. Li; |
| 27 | Constrained Route Planning Over Large Multi-Modal Time-Dependent Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes an approach for CRP over multi-modal time-dependent networks. |
Y. Wang; Y. Yuan; H. Wang; X. Zhou; C. Mu; G. Wang; |
| 28 | Online Route Planning Over Time-Dependent Road Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we study the online route planning over time-dependent road networks (ORPTD). |
D. Chen; Y. Yuan; W. Du; Y. Cheng; G. Wang; |
| 29 | Dynamic Hub Labeling for Road Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we adopt the state-of-the-art tree decomposition-based hub labeling as the underlying index, and design efficient algorithms to incrementally maintain the index. |
M. Zhang; L. Li; W. Hua; R. Mao; P. Chao; X. Zhou; |
| 30 | An Effective Joint Prediction Model for Travel Demands and Traffic Flows Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study how to jointly predict travel demands and traffic flows for all regions of a city at a future time interval. |
H. Yuan; G. Li; Z. Bao; L. Feng; |
| 31 | A Learning-based Method for Computing Shortest Path Distances on Road Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a hierarchical model to represent the embedding, and design an effective method to train the model. |
S. Huang; Y. Wang; T. Zhao; G. Li; |
| 32 | Efficient Federated-Learning Model Debugging Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we try to tackle this challenging issue by introducing the first FL debugging framework, FLDebugger, for mitigating test error caused by erroneous training data. |
A. Li; et al. |
| 33 | Communication-efficient Decentralized Machine Learning Over Heterogeneous Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a decentralized approach, namely NetMax, that enables worker nodes to communicate via high-speed links and, thus, significantly speed up the training process. |
P. Zhou; Q. Lin; D. Loghin; B. C. Ooi; Y. Wu; H. Yu; |
| 34 | Spark-based Cloud Data Analytics Using Multi-Objective Optimization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents UDAO, a Spark-based Unified Data Analytics Optimizer that can automatically determine a cluster configuration with a suitable number of cores as well as other system parameters that best meet the task objectives. |
F. Song; et al. |
| 35 | WedgeChain: A Trusted Edge-Cloud Store With Asynchronous (Lazy) Trust Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose WedgeChain, a data store that spans both edge and cloud nodes (an edge-cloud system). |
F. Nawab; |
| 36 | CooLSM: Distributed and Cooperative Indexing Across Edge and Cloud Machines Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Cooperative LSM (CooLSM), a distributed Log-Structured Merge Tree that is designed to overcome the unique challenges of edge-cloud indexing such as machine and workload heterogeneity and the communication latency asymmetry between the edge and the cloud. |
N. Mittal; F. Nawab; |
| 37 | Interactive Analytic DBMSs: Breaching The Scalability Wall Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes how an analytic DBMS optimized for low-latency queries can breach the scalability wall by sharding different tables to different subsets of cluster nodes ? a strategy we call partial sharding ? and reduce the query fan-out. |
P. Pedreira; et al. |
| 38 | Relational Header Discovery Using Similarity Search in A Table Corpus Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a fully automated, multi-phase system that discovers table column headers for cases where headers are missing, meaningless, or unrepresentative for the column values. |
H. Harmouch; T. Papenbrock; F. Naumann; |
| 39 | Efficient Joinable Table Discovery in Data Lakes: A High-Dimensional Similarity-Based Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose PEXESO, a framework for joinable table discovery in data lakes. |
Y. Dong; K. Takeoka; C. Xiao; M. Oyamada; |
| 40 | Valentine: Evaluating Matching Techniques for Dataset Discovery Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to rectify the problem of evaluating the effectiveness and efficiency of schema matching methods for the specific needs of dataset discovery. |
C. Koutras; et al. |
| 41 | Odess: Speeding Up Resemblance Detection for Redundancy Elimination By Fast Content-Defined Sampling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we focus on similarity-based delta compression, which calculates and stores the difference of very similar, but non-duplicate, chunks in storage systems. |
X. Zou; et al. |
| 42 | Latent Low-rank Graph Learning for Multimodal Clustering Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these issues, we propose a novel multimodal subspace clustering method via adaptively learning a similarity graph on a latent low-rank representation space. |
G. Zhong; C. -M. Pun; |
| 43 | Hate Is The New Infodemic: A Topic-aware Modeling of Hate Speech Diffusion on Twitter Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we focus on exploring user behavior, which triggers the genesis of hate speech on Twitter and how it diffuses via retweets. |
S. Masud; et al. |
| 44 | UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we first introduce a new and efficient edge sampler based on Metropolis-Hastings sampling technique, and theoretically show the convergence property of the edge sampler to arbitrary discrete probability distributions. Then we propose a random walk model abstraction, in which users can easily define different transition probability by specifying dynamic edge weights and random walk states. |
X. Yao; Y. Shao; B. Cui; L. Chen; |
| 45 | Towards Efficient Motif-based Graph Partitioning: An Adaptive Sampling Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the problem of efficient motif-based graph partitioning (MGP). |
S. Huang; Y. Li; Z. Bao; Z. Li; |
| 46 | LineageBA: A Fast, Exact and Scalable Graph Generation for The Barab�si-Albert Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a fast, exact, and scalable graph generation method called LineageBA that solves the above issue. |
H. Park; M. -S. Kim; |
| 47 | Search to Aggregate Neighborhood for Graph Neural Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, to obtain the data-specific GNN architectures and address the computational challenges facing by NAS approaches, we propose a framework, which tries to Search to Aggregate NEighborhood (SANE), to automatically design data-specific GNN architectures. |
H. ZHAO; Q. YAO; W. TU; |
| 48 | FastSGG: Efficient Social Graph Generation Using A Degree Distribution Generation Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to accelerate the graph generation process, a degree distribution generation (D2G) model is proposed. |
C. Wang; B. Wang; B. Huang; S. Song; Z. Li; |
| 49 | Noah: Neural-optimized A* Search Algorithm for Graph Edit Distance Computation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel approach Noah, which combines A* search algorithm and graph neural networks to compute approximate GED in a more effective and intelligent way. |
L. Yang; L. Zou; |
| 50 | TS-Benchmark: A Benchmark for Time Series Databases Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce such a benchmark called TS-Benchmark which majorly applies a scenario of device monitoring for wind turbines. |
Y. Hao; et al. |
| 51 | DBA Bandits: Self-driving Index Tuning Under Ad-hoc, Analytical Workloads with Safety Guarantees Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a self-driving approach to online index selection that eschews the DBA and query optimiser, and instead learns the benefits of viable structures through strategic exploration and direct performance observation. |
R. M. Perera; B. Oetomo; B. I. P. Rubinstein; R. Borovica-Gajic; |
| 52 | Less Is More: De-amplifying I/Os for Key-value Stores with A Log-assisted LSM-tree Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel scheme, called Log-assisted LSM-tree (L2SM), to fundamentally address the long-existing I/O amplification problem. |
K. Huang; Z. Jia; Z. Shen; Z. Shao; F. Chen; |
| 53 | Multidimensional Adaptive & Progressive Indexes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Given that not all of them can be achieved at the same time, we present three novel incremental multidimensional indexing techniques that represent three sample points on a Pareto front for this multi-objective optimization problem. |
M. A. Nerone; P. Holanda; E. C. de Almeida; S. Manegold; |
| 54 | Hash Adaptive Bloom Filter Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the above problems, we propose a new Hash Adaptive Bloom Filter (HABF) that supports the customization of hash functions for keys. |
R. Xie; et al. |
| 55 | HST+: An Efficient Index for Embedding Arbitrary Metric Spaces Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For insertion of new points, we propose a new data structure, called Hierarchically Separated Forest (HSF), i.e., a collection of HSTs. |
Y. Zeng; Y. Tong; L. Chen; |
| 56 | Flow Computation in Temporal Interaction Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the flow computation problem between two vertrices in an interaction network. |
C. Kosyfaki; N. Mamoulis; E. Pitoura; P. Tsaparas; |
| 57 | Leveraging Temporal and Topological Selectivities in Temporal-clique Subgraph Query Processing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an approach that takes full advantage of both topological and temporal selectivities during the processing of temporal-clique subgraph queries. |
K. Zhu; G. Fletcher; N. Yakovets; |
| 58 | Trajectory Simplification with Reinforcement Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to learn a policy for the decision making tasks via reinforcement learning (RL) and develop trajectory simplification methods based on the learned policy. |
Z. Wang; C. Long; G. Cong; |
| 59 | E2DTC: An End to End Deep Trajectory Clustering Framework Via Self-Training Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose an end-to-end deep trajectory clustering framework via self-training, termed as E2DTC, inspired by the data-driven capabilities of deep neural networks. |
Z. Fang; Y. Du; L. Chen; Y. Hu; Y. Gao; G. Chen; |
| 60 | REPOSE: Distributed Top-k Trajectory Similarity Search with Local Reference Point Tries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a distributed in-memory management framework called REPOSE for processing top-k trajectory similarity queries on Spark. |
B. Zheng; L. Weng; X. Zhao; K. Zeng; X. Zhou; C. S. Jensen; |
| 61 | Durable Top-K Instant-Stamped Temporal Records with User-Specified Scoring Functions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose new algorithms for solving this problem, and provide a comprehensive theoretical analysis on the complexities of the problem itself and of our algorithms. |
J. Gao; S. Sintos; P. K. Agarwal; J. Yang; |
| 62 | The Case for In-Memory OLAP on Wimpy Nodes Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we challenge the conventional wisdom that high-end hardware is absolutely necessary for state-of-the-art performance and instead advocate for a radically different approach based on cheap single-board computers (SBCs). |
A. Crotty; A. Galakatos; C. Luckett; U. Cetintemel; |
| 63 | DyCuckoo: Dynamic Hash Tables on GPUs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel dynamic cuckoo hash table technique on GPUs, known as DyCuckoo. |
Y. Li; Q. Zhu; Z. Lyu; Z. Huang; J. Sun; |
| 64 | Programming An SSD Controller to Support Batched Writes for Variable-Size Pages Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This current work is a major redesign to support a batched write interface with variable size pages. |
J. Do; C. Luo; D. Lomet; |
| 65 | Predict and Write: Using K-Means Clustering to Extend The Lifetime of NVM Storage Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this challenge, we propose Predict and Write (PNW), a K/V-store that uses a clustering-based machine learning approach to extend the lifetime of NVMs. |
S. Kargar; H. Litz; F. Nawab; |
| 66 | Discriminative Admission Control for Shared-everything Database Under Mixed OLTP Workloads Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To achieve the optimal performance for each kind of transaction, we design a discriminative admission control mechanism for shared-everything database, referred to as DAC. |
D. Wang; P. Cai; W. Qian; A. Zhou; |
| 67 | Efficiently Reclaiming Space in A Log Structured Store Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We analyze cleaning performance and introduce a cleaning strategy that uses a new way to prioritize the order in which segments are cleaned. |
D. Lomet; C. Luo; |
| 68 | LogLog Filter: Filtering Cold Items Within A Large Range Over High Speed Data Streams Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the problem of computing item frequencies, finding top-k hot items, and detecting heavy changes. |
P. Jia; P. Wang; J. Zhao; Y. Yuan; J. Tao; X. Guan; |
| 69 | SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose SLICENSTITCH for continuous CANDECOMP/PARAFAC (CP) decomposition, which has numerous time-critical applications, including anomaly detection, recommender systems, and stock market prediction. |
T. Kwon; I. Park; D. Lee; K. Shin; |
| 70 | DISC: Density-Based Incremental Clustering By Striding Over Streaming Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new incremental density-based clustering algorithm called DISC optimized for the sliding window model. |
B. Kim; K. Koo; J. Kim; B. Moon; |
| 71 | Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and Outliers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we answer this question by introducing SOFIA, a robust factorization method for real-world tensor streams. |
D. Lee; K. Shin; |
| 72 | Single Point Incremental Fourier Transform on 2D Data Streams Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose the Single Point Incremental Fourier Transform (SPIFT), a novel incremental algorithm to produce sequences of sky images. |
M. Saad; A. Bernstein; M. H. B�hlen; D. Dell�Aglio; |
| 73 | SALSA: Self-Adjusting Lean Streaming Analytics Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a simple and general method called SALSA for dynamic re-sizing of counters, and show its effectiveness. |
R. B. Basat; G. Einziger; M. Mitzenmacher; S. Vargaftik; |
| 74 | NewsLink: Empowering Intuitive News Search with Knowledge Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel news search framework, called NEWSLINK, to empower intuitive news search by using relationship paths discovered from open Knowledge Graphs (KGs). |
Y. Yang; Y. Li; A. K. H. Tung; |
| 75 | On Disambiguating Authors: Collaboration Network Reconstruction in A Bottom-up Manner Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we model the author disambiguation as a collaboration network reconstruction problem, and propose an incremental and unsupervised author disambiguation method, namely IUAD, which performs in a bottom-up manner. |
N. Li; et al. |
| 76 | A Bootstrapping Approach to Optimize Random Walk Based Statistical Estimation Over Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper develops an algorithmic framework to reduce the mean square error of such statistical estimation. |
P. Yi; H. Xie; Y. Li; J. C. S. Lui; |
| 77 | Leveraging Meta-path Contexts for Classification in Heterogeneous Information Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these problems, we propose ConCH, a graph neural network model. |
X. Li; D. Ding; B. Kao; Y. Sun; N. Mamoulis; |
| 78 | Property Graph Schema Optimization for Domain-Specific Knowledge Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that graph schema design has significant impact on query performance, and propose two algorithms to generate an optimized property graph schema from the domain ontology. |
R. Alotaibi; C. Lei; A. Quamar; V. Efthymiou; F. �zcan; |
| 79 | Fast Core-based Top-k Frequent Pattern Discovery in Knowledge Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study a core-based top-k frequent pattern discovery problem which is frequently used as a subroutine in analyzing knowledge graphs. |
J. Zeng; L. H. U; X. Yan; M. Han; B. Tang; |
| 80 | The Logarithmic Dynamic Cuckoo Filter Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel data structure for dynamic big data sets, called logarithmic dynamic cuckoo filter (LDCF). |
F. Zhang; H. Chen; H. Jin; P. Reviriego; |
| 81 | Continuously Bulk Loading Over Range Partitioned Tables for Large Scale Historical Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a learning-based framework, referred to as LeaBalancer, to balance the merge loads across cluster nodes. |
X. He; P. Cai; X. Zhou; A. Zhou; |
| 82 | Eclipse: Generalizing KNN and Skyline Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To process eclipse queries, we propose a baseline algorithm with time complexity O(n22d-1), and an improved O(nlogd-1n) time transformationbased algorithm, where n is the number of points and d is the number of dimensions. |
J. Liu; L. Xiong; Q. Zhang; J. Pei; J. Luo; |
| 83 | Memory-Efficient Key/Foreign-Key Join Size Estimation Via Multiplicity and Intersection Size Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a technique to estimate the size of a key/foreign-key join of two filtered relations. |
M. M�ller; D. Flachs; G. Moerkotte; |
| 84 | Authenticated Keyword Search in Scalable Hybrid-Storage Blockchains Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study novel ADS schemes for authenticated keyword search in hybrid-storage blockchains. |
C. Zhang; C. Xu; H. Wang; J. Xu; B. Choi; |
| 85 | NestGPU: Nested Query Processing on GPU Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our approach is general-purpose and GPU-acceleration based, aiming for high performance at a minimum development cost. |
S. Floratos; et al. |
| 86 | Aria: Tolerating Skewed Workloads in Secure In-memory Key-value Stores Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present Aria, a secure in-memory KV store based on SGX. |
F. Yang; Y. Chen; Y. Lu; Q. Wang; J. Shu; |
| 87 | CruiseDB: An LSM-Tree Key-Value Store with Both Better Tail Throughput and Tail Latency Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Unlike the I/O isolation or prioritization methods that cannot solve the SLA problem thoroughly, we have designed and implemented a new SLA-oriented LSM-tree KV store, i.e., CruiseDB, to solve both the essential and the direct SLA problems of LSM-tree KV stores by introducing an adaptive admission mechanism and improving the LSM-tree structure. |
J. Liang; Y. Chai; |
| 88 | FPGA for Aggregate Processing: The Good, The Bad, and The Ugly Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on current CPU-FPGA architectures and study their usability for database management systems. |
Z. F. Eryilmaz; A. Kakaraparthy; J. M. Patel; R. Sen; K. Park; |
| 89 | Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose FiCSUM, a general framework to represent both supervised and unsupervised behaviours of a concept in a fingerprint, a vector of many distinct meta-information features able to uniquely identify more concepts. |
B. Halstead; Y. S. Koh; P. Riddle; M. Pechenizkiy; A. Bifet; R. Pears; |
| 90 | Concept Drift Detection from Multi-Class Imbalanced Data Streams Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a detailed taxonomy of challenges posed by concept drift in multi-class imbalanced data streams, as well as a novel trainable concept drift detector based on Restricted Boltzmann Machine. |
L. Korycki; B. Krawczyk; |
| 91 | DisMASTD: An Efficient Distributed Multi-Aspect Streaming Tensor Decomposition Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose DisMASTD, an efficient distributed multi-aspect streaming tensor decomposition. |
K. Yang; Y. Gao; Y. Shen; B. Zheng; L. Chen; |
| 92 | EDGE: Entity-Diffusion Gaussian Ensemble for Interpretable Tweet Geolocation Prediction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our paper presents a tweet geolocation prediction framework, EDGE (Entity-Diffusion Gaussian Ensemble), which delivers predictions that are both accurate and highly interpretable without requiring any additional contextual information such as user profile and location history. |
B. Hui; H. Chen; D. Yan; W. -S. Ku; |
| 93 | Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, observing that existing scoring functions can exhibit distinct performance on different semantic patterns, we are motivated to explore such semantics by searching relationa-ware scoring functions. |
S. DI; Q. YAO; Y. ZHANG; L. CHEN; |
| 94 | INFOSHIELD: Generalizable Information-Theoretic Human-Trafficking Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present INFOSHIELD, which makes the following contributions: (a) Practical, being scalable and effective on real data, (b) Parameter-free and Principled, requiring no user-defined parameters, (c) Interpretable, finding a document to be the cluster representative, highlighting all the common phrases, and automatically detecting slots, i.e. phrases that differ in every document; and (d) Generalizable, beating or matching domain-specific methods in Twitter bot detection and human trafficking detection respectively, as well as being language-independent finding clusters in Spanish, Italian, and Japanese. |
M. -C. Lee; et al. |
| 95 | An Efficient Approach for Cross-Silo Federated Learning to Rank Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the recent progress in federated learning, we propose a novel framework named Cross-Silo Federated Learning-to-Rank (CS-F-LTR), where the efficiency issue becomes the major bottleneck. |
Y. Wang; Y. Tong; D. Shi; K. Xu; |
| 96 | Efficient Construction of Nonlinear Models Over Normalized Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the implementation of popular nonlinear ML models, Gaussian Mixture Models (GMM) and Neural Networks (NN), over normalized data addressing both cases of binary and multiway joins over normalized relations. |
Z. Cheng; N. Koudas; Z. Zhang; X. Yu; |
| 97 | Workload-aware Materialization for Efficient Variable Elimination on Bayesian Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel materialization method, which can lead to significant efficiency gains when processing inference queries using the Variable Elimination algorithm. |
C. Aslay; M. Ciaperoni; A. Gionis; M. Mathioudakis; |
| 98 | A Distance-Based Scheme for Reducing Bandwidth in Distributed Geometric Monitoring Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the Distance Scheme: a novel bandwidth-efficient variation of the GM protocol that reduces the size of most monitoring messages in GM to a single scalar, and is compatible with the large body of prior work on GM. |
Y. Alfassi; M. Gabel; G. Yehuda; D. Keren; |
| 99 | LHist: Towards Learning Multi-dimensional Histogram for Massive Spatial Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the emerging learned index techniques where the widely used index structures like B-tree can be further improved by integrating simple machine learning models, in this paper, we propose a learned data synopsis technique named Learned Multi-dimensional Histogram (LHist). |
Q. Liu; Y. Shen; L. Chen; |
| 100 | Data-Driven Fairness-Aware Vehicle Displacement for Large-Scale Electric Taxi Fleets Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by a set of findings obtained from a data-driven investigation, in this paper, we design a fairness-aware vehicle displacement system called FairMove to improve the overall profit efficiency and profit fairness of electric taxi fleets by considering both the passenger travel demand and taxi charging demand. |
G. Wang; S. Zhong; S. Wang; F. Miao; Z. Dong; D. Zhang; |
| 101 | On Efficient and Scalable Time-Continuous Spatial Crowdsourcing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study a new type of spatial crowdsourcing, called time-continuous spatial crowdsourcing (TCSC in short). |
T. Wang; X. Xie; X. Cao; T. B. Pedersen; Y. Wang; M. Xiao; |
| 102 | Spatial-Temporal Similarity for Trajectories with Location Noise and Sporadic Sampling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we consider the general and realistic sensing scenario that the locations of the trajectories may be noisy, and that these trajectories are sporadically sampled with randomness and asynchrony from the underlying continuous paths. |
G. Li; C. -C. Hung; M. Liu; L. Pan; W. -C. Peng; S. . -H. G. Chan; |
| 103 | Learning to Characterize Matching Experts Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we characterize human matching experts, those humans whose proposed correspondences can mostly be trusted to be valid. |
R. Shraga; O. Amir; A. Gal; |
| 104 | End-to-end Task Based Parallelization for Entity Resolution on Dynamic Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a framework for end-to-end ER that incrementally and efficiently produces results as heterogeneous data streams in. |
L. Gazzarri; M. Herschel; |
| 105 | KDDLog:Performance and Scalability in Knowledge Discovery By Declarative Queries with Aggregates Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show that these benefits can now be extended to predictive analytics, e.g. clustering, classification and association, by using aggregates in declarative recursive queries. |
Y. Li; J. Wang; M. Li; A. Das; J. Gu; C. Zaniolo; |
| 106 | Cost�effective Variational Active Entity Resolution Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we set out to devise an entity resolution method that builds on the robustness conferred by deep autoencoders to reduce human?involvement costs. |
A. Bogatu; N. W. Paton; M. Douthwaite; S. Davie; A. Freitas; |
| 107 | Structured Object Matching Across Web Page Revisions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present novel techniques that match tables, infoboxes and lists within a page across page revisions. |
T. Bleifu�; L. Bornemann; D. V. Kalashnikov; F. Naumann; D. Srivastava; |
| 108 | Automating Entity Matching Model Development Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Under this setting, we propose AutoML-EM-Active, investigating how to maximize the benefit of AutoML-EM with automatic data labeling. |
P. Wang; W. Zheng; J. Wang; J. Pei; |
| 109 | A Framework to Quantify Approximate Simulation on Graph Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we first present several properties necessary for a fractional ?-simulation measure. Then, we present FSim ? , a general fractional ?-simulation computation framework that can be configured to quantify the extent of all ?-simulations. |
X. Chen; L. Lai; L. Qin; X. Lin; B. Liu; |
| 110 | PEFP: Efficient K-hop Constrained S-t Simple Path Enumeration on FPGA Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this, in this paper, we propose the first FPGA-based algorithm PEFP to solve the problem of k-hop constrained s-t simple path enumeration efficiently. |
Z. Lai; Y. Peng; S. Yang; X. Lin; W. Zhang; |
| 111 | DPTL+: Efficient Parallel Triangle Listing on Batch-Dynamic Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to fill this gap by developing novel and efficient parallel solutions. |
M. Yu; L. Qin; Y. Zhang; W. Zhang; X. Lin; |
| 112 | Finding A Summary for All Maximal Cliques Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As a result, in order to provide the best study of the problem, we propose four strategies in two directions to speed up the process of finding a maximal clique summary by (1) restricting the bound calculation operation to a particular subset of all search branches and (2) making the best use of the bounds that have been previously calculated. |
X. Li; et al. |
| 113 | An Efficient Algorithm for The Anchored K-Core Budget Minimization Problem Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we define and study the anchored k-core budget minimization problem. |
K. Liu; S. Wang; Y. Zhang; C. Xing; |
| 114 | Scalable Graph Isomorphism: Combining Pairwise Color Refinement and Backtracking Via Compressed Candidate Space Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new approach to graph isomorphism, which is the framework of pairwise color refinement and efficient backtracking. |
G. Gu; Y. Nam; K. Park; Z. Galil; G. F. Italiano; W. -S. Han; |
| 115 | Scalable Model-Based Management of Correlated Dimensional Time Series in ModelarDB+ Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As a remedy, we present a model-based approach for managing time series with dimensions that exploits correlation in and among time series. |
S. K. Jensen; T. B. Pedersen; C. Thomsen; |
| 116 | RCC: Resilient Concurrent Consensus for High-Throughput Secure Transaction Processing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To push throughput beyond this single-replica limit, we propose concurrent consensus. |
S. Gupta; J. Hellings; M. Sadoghi; |
| 117 | WipDB: A Write-in-place Key-value Store That Mimics Bucket Sort Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a KV store design that leverages relatively stable key distributions to bound the write amplification by a number as low as 4.15 in practice. |
X. Zhao; S. Jiang; X. Wu; |
| 118 | Lock Violation for Fault-tolerant Distributed Database System* Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Instead, we introduce Distributed Lock Violation (DLV), a specialized speculative technique for geo-replicated distributed databases. |
H. Guo; X. Zhou; L. Cai; |
| 119 | Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Mitos, a system that achieves the best of both worlds: it achieves both high performance and ease-of-use. Mitos uses an intermediate representation that abstracts away specific control flow statements and is able to represent any imperative control flow. |
G. E. G�vay; T. Rabl; S. Bre�; L. Madai-Tahy; J. -A. Quian�-Ruiz; V. Markl; |
| 120 | Samya: A Geo-Distributed Data System for High Contention Aggregate Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose an alternate data management system, Samya, to manage aggregate cloud resource usage data. |
S. Maiyya; I. Ahmad; D. Agrawal; A. E. Abbadi; |
| 121 | FAST: FPGA-based Subgraph Matching on Massive Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim at scaling up subgraph matching on a single machine using FPGAs. |
X. Jin; Z. Yang; X. Lin; S. Yang; L. Qin; Y. Peng; |
| 122 | A+ Indexes: Tunable and Space-Efficient Adjacency Lists in Graph Database Management Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe a new tunable indexing subsystem for GDBMSs, we call A+ indexes, with materialized view support. |
A. Mhedhbi; P. Gupta; S. Khaliq; S. Salihoglu; |
| 123 | Explaining Missing Data in Graphs: A Constraint-based Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a constraint-based approach to clarify missing values in graphs. |
Q. Song; P. Lin; H. Ma; Y. Wu; |
| 124 | Influence Maximization Based on Dynamic Personal Perception in Knowledge Graph Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, by exploiting the knowledge graph (KG) to capture dynamic user perception, we formulate the problem of Influence Maximization based on Dynamic Personal Perception (IMDPP) that considers user preferences and social influence reflecting the impact of relevant item adoptions. |
Y. -W. Teng; Y. Shi; C. -H. Tai; D. -N. Yang; W. -C. Lee; M. -S. Chen; |
| 125 | Privacy Preserving Strong Simulation Queries on Large Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We transform the core of the existing strong simulation algorithm using data-oblivious operations (ObSSA) and propose its secure version. |
L. Xu; J. Jiang; B. Choi; J. Xu; S. S. Bhowmick; |
| 126 | Trillion-scale Graph Processing Simulation Based on Top-Down Graph Upscaling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a concept of graph processing simulation, a single-step approach that generates a graph and processes a graph algorithm simultaneously. |
H. Park; J. Xiong; M. -S. Kim; |
| 127 | Multi-Facet Recommender Networks with Spherical Optimization Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To capture the multiple facets of user preferences and item properties while resolving their potential conflicts, we propose the novel framework of Multi-fAcet Recommender networks with Spherical optimization (MARS). |
Y. Tan; C. Yang; X. Wei; Y. Ma; X. Zheng; |
| 128 | Group-Buying Recommendation for Social E-Commerce Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we take the first step to approach the problem of group-buying recommendation for social e-commerce and develop a GBGCN method (short for Group-Buying Graph Convolutional Network). |
J. Zhang; C. Gao; D. Jin; Y. Li; |
| 129 | Reliable Recommendation with Review-level Explanations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a model, Reliable Recommendation with Review-level Explanations (RRRE), which detects reliable reviews and improves the performance of the explainable recommendation system as well. |
Y. Lyu; H. Yin; J. Liu; M. Liu; H. Liu; S. Deng; |
| 130 | Variational Self-attention Network for Sequential Recommendation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new Variational Self-Attention Network (VSAN), which introduces a variational autoencoder (VAE) into the self-attention network to capture latent user preferences. |
J. Zhao; P. Zhao; L. Zhao; Y. Liu; V. S. Sheng; X. Zhou; |
| 131 | Knowledge-Aware Group Representation Learning for Group Recommendation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce knowledge graph into group recommendation as side information, and propose a novel end-to-end method named knowledge graph-based attentive group recommendation (KGAG) to solve the data sparsity and preference aggregation problems. |
Z. Deng; C. Li; S. Liu; W. Ali; J. Shao; |
| 132 | Attacking Black-box Recommendations Via Copying Cross-domain User Profiles Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a novel framework CopyAttack. It is a reinforcement learning based black-box attacking method that harnesses real users from a source domain by copying their profiles into the target domain with the goal of promoting a subset of items. |
W. Fan; et al. |
| 133 | Approximating Multidimensional Range Counts with Maximum Error Guarantees Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We address the problem of compactly approximating multidimensional range counts with a guaranteed maximum error and propose a novel histogram-based summary structure, termed SliceHist. |
M. Shekelyan; A. Dign�s; J. Gamper; M. Garofalakis; |
| 134 | LATEST: Learning-Assisted Selectivity Estimation Over Spatio-Textual Streams Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes LATEST; a system module that uses machine learning to enable dynamic adaptation of estimation data structures. |
M. Patil; A. Magdy; |
| 135 | ProMIPS: Efficient High-Dimensional C-Approximate Maximum Inner Product Search with A Lightweight Index Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we relax the guarantee of accuracy for efficiency and propose an efficient method for c-Approximate Maximum Inner Product (c-AMIP) search with a lightweight iDistance index. |
Y. Song; Y. Gu; R. Zhang; G. Yu; |
| 136 | A Fully Dynamic Algorithm for K-Regret Minimizing Sets Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose the first fully-dynamic algorithm for the k-RMS problem that can efficiently provide the up-to-date result w.r.t. any tuple insertion and deletion in the database with a provable guarantee. |
Y. Wang; Y. Li; R. C. -W. Wong; K. -L. Tan; |
| 137 | Optimizing Error-Bounded Lossy Compression for Scientific Data By Dynamic Spline Interpolation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel error-bounded lossy compressor based on a state-of-the-art prediction-based compression framework. |
K. Zhao; S. Di; M. Dmitriev; T. -L. D. Tonellot; Z. Chen; F. Cappello; |
| 138 | MLCask: Efficient Management of Component Evolution in Collaborative Data Analytics Pipelines Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we identify two main challenges that arise during the deployment of machine learning pipelines, and address them with the design of versioning for an end-to-end analytics system MLCask. |
Z. Luo; et al. |
| 139 | Improving Constrained Search Results By Data Melioration Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We prove PCS to be hard to approximate, and consequently propose a best-effort PTIME heuristic to solve it. |
I. Guy; T. Milo; S. Novgorodov; B. Youngmann; |
| 140 | G-TADOC: Enabling Efficient GPU-Based Text Analytics Without Decompression Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe G-TADOC, the first framework that provides GPU-based text analytics directly on compression, effectively enabling efficient text analytics on GPUs without decompressing the input data.G-TADOC solves three major challenges. |
F. Zhang; et al. |
| 141 | Fast Similarity Computation for T-SNE Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our proposal, F-tSNE, reduces the computation cost of random walk-based t-SNE by computing the LDL decomposition for the graph Laplacian based on two ideas: (1) reducing non-zero elements in the LDL decomposition by using a reordering matrix and (2) exploiting the sparse structure of the graph when computing the similarities. |
Y. Fujiwara; Y. Ida; S. Kanai; A. Kumagai; N. Ueda; |
| 142 | Rapid Approximate Aggregation with Distribution-Sensitive Interval Guarantees Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop a CI technique that is both correct and tighter than traditional approaches. |
S. Macke; M. Aliakbarpour; I. Diakonikolas; A. Parameswaran; R. Rubinfeld; |
| 143 | Optimally Summarizing Data By Small Fact Sets for Concise Answers to Voice Queries Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal is to find combinations of facts that optimally summarize data sets. |
I. Trummer; C. Anderson; |
| 144 | Automatic Webpage Briefing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To preserve more knowledge of seen domains and to better utilize the location patterns, we propose a Dual Distillation model which consists of identification distillation (ID) and understanding distillation (UD); ID distills knowledge on the identification of informative contents under the guidance of the learned topics of seen domains, while UD distills knowledge on topic generation or key attribute extraction. |
Y. Dai; R. Zhang; J. Qi; |
| 145 | EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specifically, we propose two plugin neural networks that are able to better capture distinct temporal dynamics for different entities and dynamic entity correlations across time, so that forecasting accuracy is improved while model parameters to be learned are reduced. |
R. -G. Cirstea; T. Kieu; C. Guo; B. Yang; S. J. Pan; |
| 146 | Forecasting Ambulance Demand with Profiled Human Mobility Via Heterogeneous Multi-Graph Neural Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we are therefore motivated to mine the collective daily routines in human mobility, to further represent the evolving spatial correlations. |
Z. Wang; et al. |
| 147 | Efficient Constrained Shortest Path Query Answering with Forest Hop Labeling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel skyline path concatenation approach to avoid the expensive skyline path search, which is then used to efficiently construct a 2-hop labeling index for the CSP queries. |
Z. Liu; L. Li; M. Zhang; W. Hua; P. Chao; X. Zhou; |
| 148 | TASM: A Tile-Based Storage Manager for Video Analytics Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We design, implement, and evaluate TASM, a new tile-based storage manager for video data. |
M. Daum; B. Haynes; D. He; A. Mazumdar; M. Balazinska; |
| 149 | A Two-layer Partitioning for Non-point Spatial Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a secondary partitioning technique for space-oriented partitioning indices (e.g., grids), which improves their performance significantly, by avoiding the generation and elimination of duplicate results. |
D. Tsitsigkos; K. Lampropoulos; P. Bouros; N. Mamoulis; M. Terrovitis; |
| 150 | Spangle: A Distributed In-Memory Processing System for Large-Scale Arrays Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce an array processing system called Spangle. |
S. Kim; B. Kim; B. Moon; |
| 151 | Memory-Efficient Database Fragment Allocation for Robust Load Balancing When Nodes Fail Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present an optimal approach and a scalable heuristic, based on three mutually supportive linear programming models, to calculate memory-efficient fragment allocations that guarantee to distribute the workload evenly – even in the case of node failures. |
S. Halfpap; R. Schlosser; |
| 152 | An Empirical Experiment on Deep Learning Models for Predicting Traffic Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we conduct two experiments to answer the two questions. In the first experiment, we conduct an experiment with the state-of-the-art models and the identical public datasets to compare model performance under a consistent experiment environment. We then extract a set of temporal regions in the datasets, whose speeds change abruptly and use these regions to explore model performance with difficult intervals. |
H. Lee; C. Park; S. Jin; H. Chu; J. Choo; S. Ko; |
| 153 | Evaluating List Intersection on SSDs for Parallel I/O Skipping Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To understand the impact of SSDs to list intersection, in this work, we tune existing in-memory intersection algorithms to be SSD-aware with the idea of parallel I/O skipping, and experimentally evaluate them on synthetic and real datasets. |
J. Wang; C. Lin; Y. Papakonstantinou; S. Swanson; |
| 154 | Performance Characterization of HTAP Workloads Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we characterize workload interference for HTAP systems. |
U. Sirin; S. Dwarkadas; A. Ailamaki; |
| 155 | Accelerating The Yinyang K-Means Algorithm Using The GPU Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this context, this paper: (i) proposes the first GPU-accelerated Yinyang algorithm in the literature; (ii) advances several optimizations to GPU kernels; (iii) contrasts and evaluates different degrees of distance calculation pruning; and, (iv) compares the performance of our GPU-accelerated Yinyang algorithm to four reference implementations. |
C. Taylor; M. Gowanlock; |
| 156 | SLIMSTORE: A Cloud-based Deduplication System for Multi-version Backups Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose two types of processing nodes with different design focuses to meet the needs of cloud-based backup. |
Z. Zhang; et al. |
| 157 | Meepo: Sharded Consortium Blockchain Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Facing these challenges, we propose Meepo, a systematic study on sharded consortium blockchain. |
P. Zheng; Q. Xu; Z. Zheng; Z. Zhou; Y. Yan; H. Zhang; |
| 158 | SciChain: Blockchain-enabled Lightweight and Efficient Data Provenance for Reproducible Scientific Computing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper advocates leveraging blockchains to deliver immutable and autonomous data provenance services such that scientific discoveries are trustworthy. |
A. Al-Mamun; F. Yan; D. Zhao; |
| 159 | Accelerating Similarity-based Mining Tasks on High-dimensional Data By Processing-in-memory Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we tackle the above challenge and carefully exploit NVM PIM to accelerate similarity-based mining tasks on multi-dimensional data without compromising the accuracy of results. |
F. Wang; M. L. Yiu; Z. Shao; |
| 160 | DS2: Handling Data Skew Using Data Stealings Over High-Speed Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we divide data skew in distributed data processing systems into intra-node and inter-node skew. |
Z. He; Z. Li; X. Peng; C. Weng; |
| 161 | Efficient Matrix Factorization on Heterogeneous CPU-GPU Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Due to the large computational cost of MF, we aim to improve the efficiency of SGD-based MF computation by utilizing the massive parallel processing power of heterogeneous multiprocessors. |
Y. Yu; D. Wen; Y. Zhang; X. Wang; W. Zhang; X. Lin; |
| 162 | Rethink The Linearizability Constraints of Raft for Distributed Key-Value Stores Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we rethink these constraints in-depth and find that some of them are not necessary, and can be broken to accelerate the performance significantly without breaking the linear consistency for distributed key-value storage systems. |
Y. Wang; Z. Wang; Y. Chai; X. Wang; |
| 163 | SING: Sequence Indexing Using GPUs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose SING, the first data series index designed to take advantage of Graphics Processing Units (GPUs). |
B. Peng; P. Fatourou; T. Palpanas; |
| 164 | TLBtree: A Read/Write-Optimized Tree Index for Non-Volatile Memory Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, in this paper, we propose a read/write-optimized tree index called TLBtree (Two-Layer B+-tree) for NVM. |
Y. Luo; P. Jin; Q. Zhang; B. Cheng; |
| 165 | Utilizing Delta Trees for Efficient, Iterative Exploration and Transformation of Semi-Structured Contents Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we extend our prior work on JODA, a vertically scalable, versatile JSON data processor, to make use of so-called delta trees for the succinct representation of incrementally created query results. |
N. Sch�fer; S. Michel; |
| 166 | Joint Index, Sorting, and Compression Optimization for Memory-Efficient Spatio-Temporal Data Management Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a linear programming approach to determine fine-grained configuration decisions for spatio-temporal workloads. |
K. Richly; R. Schlosser; M. Boissier; |
| 167 | High-Performance Smart Contracts Concurrent Execution for Permissioned Blockchain Using SGX Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new two-phase framework based on trusted hardware Intel SGX, which can avoid the re-execution of all smart contracts on all nodes and improve parallelism between nodes. |
M. Fang; Z. Zhang; C. Jin; A. Zhou; |
| 168 | Estimating The Extent of The Effects of Data Quality Through Observations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe a system and its implementation that computes this extended form of data quality through a principled approach of systematic noise generation and task result evaluation. |
D. Foroni; M. Lissandrini; Y. Velegrakis; |
| 169 | Decoupled Instance-label Extreme Multi-label Classification with Skew Coordinate Feature Space Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose DilXML, an extreme multi-label classifier that suggests a reasonable number of labels for each instance. |
J. Song; B. Moon; |
| 170 | Hierarchical Tree-based Sequential Event Prediction with Application in The Aviation Accident Report Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to solve this issue by taking advantage of the multi-level or hierarchical representation of these rare events. |
X. Zhao; H. Yan; Y. Liu; |
| 171 | Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the strength of graph neural networks for structured data modeling, this work proposes a Graph Neural Multi-Behavior Enhanced Recommendation (GNMR) framework which explicitly models the dependencies between different types of user-item interactions under a graph-based message passing architecture. |
L. Xia; C. Huang; Y. Xu; P. Dai; M. Lu; L. Bo; |
| 172 | Ranking Data Slices for ML Model Validation: A Shapley Value Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we tackle this challenging problem by proposing a novel game theoretic framework building upon Shapley value concept to derive a rank order for a given collection of data slices. |
E. Farchi; R. Narayanam; L. Nagalapatti; |
| 173 | From Minimum Change to Maximum Density: On S-Repair Under Integrity Constraints Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this sense, our study proposes to return the S-repair under integrity constraints with the highest density, among various minimal removal sets. |
Y. Sun; S. Song; |
| 174 | Managing Consent for Data Access in Shared Databases Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this, we propose a novel framework for actively procuring consent in shared databases, focusing on the relational model and SPJU queries. |
O. Drien; A. Amarilli; Y. Amsterdamer; |
| 175 | Summarizing Provenance of Aggregate Query Results in Relational Databases Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new approach to provenance exploration that builds on data summarization techniques. |
O. AlOmeir; E. Y. Lai; M. Milani; R. Pottinger; |
| 176 | Patterns Count-Based Labels for Datasets Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop the notion of storing a label of limited size that can be used to obtain good estimates for these counts. |
Y. Moskovitch; H. V. Jagadish; |
| 177 | PROTEUS: Predictive Explanation of Anomalies Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the following reduced-dimensionality, surrogate model approach to explain detector decisions: approximate the detection model with another one that employs only a small subset of features. |
N. Myrtakis; I. Tsamardinos; V. Christophides; |
| 178 | Ranking Desired Tuples By Database Exploration Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose DExPlorer, a system for interactive database exploration. |
X. Qin; et al. |
| 179 | CIAO: An Optimization Framework for Client-Assisted Data Loading Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present CIAO, a tunable system to enable client cooperation with the server to enable efficient partial loading and data skipping for a given workload. |
C. Ding; D. Tang; X. Liang; A. J. Elmore; S. Krishnan; |
| 180 | Optimizing Multiple Multi-Way Stream Joins Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an integer linear programming (ILP) formulation for selecting the partitioning and tuple routing with minimal probe load. |
M. Dossinger; S. Michel; |
| 181 | Updatable Materialization of Approximate Constraints Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we present a sharded bitmap as the underlying data structure which offers efficient update operations, and describe approaches to maintain approximate constraints under updates, avoiding index recomputations and full table scans. |
S. Kl�be; K. -U. Sattler; S. Baumann; |
| 182 | Ranking Papers By Their Short-Term Scientific Impact Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a method that ranks papers based on their estimated short-term impact, as measured by the number of citations received in the near future. |
I. Kanellos; T. Vergoulis; D. Sacharidis; T. Dalamagas; Y. Vassiliou; |
| 183 | Substring Similarity Search with Synonyms Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To remedy this issue, we first propose a novel similarity measure between two strings allowing substring matching with synonyms, and develop an efficient algorithm to find the strings that have a substring semantically similar to the query string. |
G. Song; K. Shim; H. Lee; |
| 184 | CaSIE: Canonicalize and Informative Selection of The OpenIE System Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an end-to-end system which takes a target incomplete KB and documents as input. |
H. Xin; X. Lin; L. Chen; |
| 185 | Node2LV: Squared Lorentzian Representations for Node Proximity Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose a new embedding model, named Node2LV, that learns the hyperbolic representations of nodes using squared Lorentzian distances. |
S. Feng; L. Chen; K. Zhao; W. Wei; F. Li; S. Shang; |
| 186 | Privacy-Preserving Sequential Publishing of Knowledge Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We remedy this problem by presenting the k w -Time-Varying Attribute Degree (k w -tad) principle that prevents adversaries from re-identifying any user appearing in w continuous anonymized KGs with a confidence higher than 1k. |
A. -T. Hoang; B. Carminati; E. Ferrari; |
| 187 | Cluster-and-Conquer: When Randomness Meets Graph Locality Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we remove this drawback with Cluster-and-Conquer (C2 for short). |
G. Giakkoupis; A. -M. Kermarrec; O. Ruas; F. Ta�ani; |
| 188 | DDHH: A Decentralized Deep Learning Framework for Large-scale Heterogeneous Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In light of this, to cope with large-scale HNE tasks with strong efficiency and effectiveness guarantee, we propose Decentralized Deep Heterogeneous Hypergraph (DDHH) embedding framework in this paper. |
M. Imran; H. Yin; T. Chen; Z. Huang; X. Zhang; K. Zheng; |
| 189 | EnsemFDet: An Ensemble Approach to Fraud Detection Based on Bipartite Graph Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an Ensemble based Fraud DETection (ENSEMFDET) method to scale up fraud detection in bipartite graphs. |
Y. Ren; H. Zhu; J. Zhang; P. Dai; L. Bo; |
| 190 | HuGE: An Entropy-driven Approach to Efficient and Scalable Graph Embeddings Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose HuGE, an efficient and scalable graph embedding method enabled by an entropy-driven mechanism. |
P. Fang; F. Wang; Z. Shi; H. Jiang; D. Feng; L. Yang; |
| 191 | Hypercore Maintenance in Dynamic Hypergraphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study exact hypercore maintenance in large-scale dynamic hypergraphs. |
Q. Luo; D. Yu; Z. Cai; X. Lin; X. Cheng; |
| 192 | Selective Edge Shedding in Large Graphs Under Resource Constraints Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this challenge, we propose selective edge shedding. |
Y. Zeng; C. Song; T. Ge; |
| 193 | Social Visibility Optimization in OSNs with Anonymity Guarantees: Modeling, Algorithms and Applications Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper considers how a user (called requester) in an OSN selects a small number of available users and invites them as new friends/followers so as to maximize his social visibility. |
S. Zheng; H. Xie; J. C. S. Lui; |
| 194 | Stealthy Targeted Data Poisoning Attack on Knowledge Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we introduce a notion of the exposure risk and propose a novel problem of attacking a KG by means of perturbations where the goal is to maximize the manipulation of the target fact?s plausibility while keeping the risk of exposure under a given budget. |
P. Banerjee; L. Chu; Y. Zhang; L. V. S. Lakshmanan; L. Wang; |
| 195 | Structure-Aware Parameter-Free Group Query Via Heterogeneous Information Network Transformer Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a new group query, namely Parameter-free Group Query (PGQ), and propose a learning-based model, called PGQN, to find a group that accommodates personalized requirements on social contexts and activity topics. |
H. -W. Chen; et al. |
| 196 | Taking Heuristic Based Graph Edge Partitioning One Step Ahead Via OffStream Partitioning Approach Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a novel OffStream partitioning approach (OSPA) and hybrid graph edge partitioner OffStreamNH. |
T. Ayall; H. Duan; C. Liu; F. Gereme; M. Abegaz; M. Deleli; |
| 197 | Fast Distributed Complex Join Processing Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the problem of co-optimize communication, pre-computing, and computation cost in one-round multiway join evaluation. |
H. Zhang; M. Qiao; J. X. Yu; H. Cheng; |
| 198 | Top-k Community Similarity Search Over Large Road-Network Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel problem, namely top-k community similarity search (Top-kCS2), which efficiently and effectively obtains spatial communities that are the most similar to a given query community over road-network graphs. |
N. Rai; X. Lian; |
| 199 | Batching and Matching for Food Delivery in Dynamic Road Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To mitigate this computational bottleneck, we develop an algorithm called FOODMATCH, which maps the vehicle assignment problem to that of minimum weight perfect matching on a bipartite graph. |
M. Joshi; A. Singh; S. Ranu; A. Bagchi; P. Karia; P. Kala; |
| 200 | Sequential Recommendation on Dynamic Heterogeneous Information Network Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We can integrate this rich information by introducing Dynamic Heterogeneous Information Networks (DHINs). |
T. Xie; Y. Xu; L. Chen; Y. Liu; Z. Zheng; |
| 201 | Towards The Smart Use of Embedding and Instance Features for Property Matching Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We therefore present a new machine learning-based property matching approach called LEAPME (LEArning-based Property Matching with Embeddings) that utilizes numerous features of both property names and instance values. |
D. Ayala; I. Hern�ndez; D. Ruiz; E. Rahm; |
| 202 | AutoOD: Neural Architecture Search for Outlier Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap, in this paper, we propose AutoOD, an automated outlier detection framework, which aims to search for an optimal neural network model within a predefined search space. |
Y. Li; et al. |
| 203 | Catching Them Red-handed: Real-time Aggression Detection on Social Media Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work introduces the first, practical, real-time framework for detecting aggression on Twitter via embracing the streaming ML paradigm. |
H. Herodotou; D. Chatzakou; N. Kourtellis; |
| 204 | Gallat: A Spatiotemporal Graph Attention Network for Passenger Demand Prediction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose a novel spatiotemporal graph attention network, namely Gallat (Graph prediction with all attention) as a solution. |
Y. Wang; et al. |
| 205 | Heterogeneous Information Assisted Bandit Learning: Theory and Application Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the HUCB algorithm to address such a challenge. |
X. Zhang; H. Xie; J. C. S. Lui; |
| 206 | Package Pick-up Route Prediction Via Modeling Couriers� Spatial-Temporal Behaviors Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel model, named DeepRoute, to predict couriers? future package pick-up routes according to the couriers? decision experience learnt from their historical spatial-temporal behaviors. |
H. Wen; et al. |
| 207 | Palette: Towards Multi-source Model Selection and Ensemble for Reuse Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the Multi-source Model Selection and Ensemble (MSMSE) problem. |
Y. Li; Y. Shen; L. Chen; |
| 208 | Querying for Interactions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Since selectivities may vary as the video evolves, we present a dynamic statistical test to determine when to trigger re-optimization of the filters. |
Y. Xarchakos; N. Koudas; |
| 209 | An Autonomous Materialized View Management System with Deep Reinforcement Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an autonomous materialized view management system, AutoView. |
Y. Han; G. Li; H. Yuan; J. Sun; |
| 210 | Revisiting Data Prefetching for Database Systems with Machine Learning Techniques Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Impressed by the enormous potential of machine learning in data management, we present an end-to-end deep learning-based framework to predict page access patterns. |
Y. Chen; Y. Zhang; J. Wu; J. Wang; C. Xing; |
| 211 | Self-Supervised Deep Metric Learning for Pointsets Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a self-supervised deep metric learning solution for pointsets. |
P. Arsomngern; C. Long; S. Suwajanakorn; S. Nutanong; |
| 212 | ValueNet: A Natural Language-to-SQL System That Learns from Database Information Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose ValueNet light and ValueNet ? two end-to-end Natural Language-to-SQL systems that incor-porate values using the challenging Spider dataset. |
U. Brunner; K. Stockinger; |
| 213 | T3S: Effective Representation Learning for Trajectory Similarity Computation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a deep learning based model, namely T3S, which embeds each trajectory (i.e., a sequence of points) into a vector (point) in a d-dimensional space, and hence can significantly accelerate the similarity computation between the trajectories. |
P. Yang; H. Wang; Y. Zhang; L. Qin; W. Zhang; X. Lin; |
| 214 | TrajForesee: How Limited Detailed Trajectories Enhance Large-scale Sparse Information to Predict Vehicle Trajectories? Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, our solution enables the ubiquitous but coarse-grained location-based surveillance information to predict the fine-grained trajectories of all vehicles with limited number of fine-grained trajectories. |
K. Shao; Y. Wang; Z. Zhou; X. Xie; G. Wang; |
| 215 | Concurrency Control Based on Transaction Clustering Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome this limitation, we propose a scheme, called transaction clustering, to decide the best isolation mechanism for any given pair of transactions automatically. |
X. Su; H. Wang; Y. Zhang; |
| 216 | A Learning to Tune Framework for LSH Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose a learning to tune framework, called LSH-tuning, which consists of a pruning model and a learning to rank model. |
X. Tang; S. Wu; G. Chen; J. Gao; W. Cao; Z. Pang; |
| 217 | TIRA in Baidu Image Advertising Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a text-image cross-modal retrieval for advertising (TIRA) model, which has been launched in Baidu image advertising. |
T. Yu; X. Yang; Y. Jiang; H. Zhang; W. Zhao; P. Li; |
| 218 | Description Generation for Points of Interest Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we first study the POI description generation problem by proposing a novel model, named as Multi Mode Description Generator (MMDG), to automatically generate description based on POIs’ reviews and other features. |
M. Zhou; J. Zhou; Y. Fu; Z. Ren; X. Wang; H. Xiong; |
| 219 | CrowdAtlas: Estimating Crowd Distribution Within The Urban Rail Transit System Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we attempt to estimate the crowd distribution within the urban rail transit system based only on the entrance and exit records of all the rail riders. |
J. E; M. Li; J. Huang; |
| 220 | DAEMON: Unsupervised Anomaly Detection and Interpretation for Multivariate Time Series Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome those limitations, in this paper, we propose an unsupervised anomaly detection framework, called DAEMON (Adversarial Autoencoder Anomaly Detection Interpretation), which performs robustly for various datasets. |
X. Chen; et al. |
| 221 | Knowledge-Based Dynamic Systems Modeling: A Case Study on Modeling River Water Quality Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a genetic model revision framework based on tree-adjoining grammar (TAG) guided genetic programming (GP), using the TAG formalism and GP operators in an effective mechanism making data-driven revisions while incorporating prior knowledge. |
N. Park; M. Kim; N. X. Hoai; R. I. Bob McKay; D. -K. Kim; |
| 222 | Collecting Geospatial Data with Local Differential Privacy for Personalized Services Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the problem of collecting the locations of individual users under LDP, and propose a perturbation mechanism designed carefully to reduce the error of each perturbed location according to the privacy budget and the domain size. |
D. Hong; W. Jung; K. Shim; |
| 223 | Experimental Study of Big Raster and Vector Database Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper draws the attention of the research community to the research problems that emerge from the concurrent processing of raster and vector data. |
S. Singla; A. Eldawy; T. Diao; A. Mukhopadhyay; E. Scudiero; |
| 224 | Predicting The Impact of Disruptions to Urban Rail Transit Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle the main challenge of abnormal data scarcity, i.e., only 6 observed disruptions in our one-year data records, we propose to format the problem into a training problem on a feature space relevant to alternative route choices of the commuters. |
X. Mo; C. Cao; M. Li; D. Z. W. Wang; |
| 225 | An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting* Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we pro-pose a novel meta-learning approach for aggregation of linearly weighted ensembles for the task of time-series forecasting. |
A. Saadallah; M. Tavakol; K. Morik; |
| 226 | Crowdrebate: An Effective Platform to Get More Rebate for Customers Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we define the Crowdrebate problem, which aims to maximize the benefit of receivers. |
W. Ni; N. Chen; P. Cheng; L. Chen; X. Lin; |
| 227 | GRAB: Finding Time Series Natural Structures Via A Novel Graph-based Scheme Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel graph-based approach, GRAB, to discover time series natural structures. |
Y. Lu; et al. |
| 228 | Near-Optimal Fixed-Route Scheduling for Crowdsourced Transit System Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider a crowdsourced bus service system (on a fixed route) that receives user requests as input and computes a scheduling of buses with flexible departure time and skip-stop to minimize the travel time of users. |
H. Li; X. Wu; L. Hou U; K. Pang Kou; |
| 229 | SPEAR: Dynamic Spatio-Temporal Query Processing Over High Velocity Data Streams Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose adaptations of principles from streaming databases, spatial data management, and distributed computing to support dynamic spatio-temporal query processing over high-velocity big data streams. |
F. Baig; D. Teng; J. Kong; F. Wang; |
| 230 | The LSM RUM-Tree: A Log Structured Merge R-Tree for Update-intensive Spatial Workloads Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we introduce the LSM RUM-tree that demonstrates the use of an Update Memo in an LSM-based R-tree to enhance the performance of the R-tree?s insert, delete, update, and search operations. |
J. Shin; J. Wang; W. G. Aref; |
| 231 | Top-k Publish/Subscribe for Ride Hitching Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on a popular carpooling service called ride hitching, which is typically implemented using a publish/subscribe approach. |
Y. Li; H. Gu; R. Chen; J. Xu; M. Xu; |
| 232 | Towards Efficient MaxBRNN Computation for Streaming Updates Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose the streamingMaxBRNNquery, which finds the optimal region to deploy a new service point when both the service points and client points are under continuous updates. |
W. Ning; X. Yan; B. Tang; |
| 233 | User Profiling Based on Nonlinguistic Audio Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this poster, we are the first to build a user profiling system to infer gender and personality based on nonlinguistic audio. |
J. Shen; O. Lederman; J. Cao; S. Tang; A. �. Pentland; |
| 234 | Semantic Search Pipeline: From Query Expansion to Concept Forging Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to increase the recall of searches, we present the Semantic Search Pipeline, a novel approach to document retrieval that uses distributional semantic models and locality sensitive hashing to expand queries and efficiently identify other relevant documents that may not contain the obvious query terms. |
E. Soper; J. Hosier; D. Bales; V. K. Gurbani; |
| 235 | Leveraging Currency for Repairing Inconsistent and Incomplete Data (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study the multiple data cleaning on incompleteness and inconsistency with currency reasoning and determination. |
X. Ding; H. Wang; J. Su; M. Wang; J. Li; H. Gao; |
| 236 | A Collective Approach to Scholar Name Disambiguation (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a collective approach, which considers the connections of different ambiguous names, such that it initially treats each author reference as a unique author entity and reformulates the bibliography data as a heterogeneous multipartite network. |
D. Luo; S. Ma; Y. Yan; C. Hu; X. Zhang; J. Huai; |
| 237 | Analyzing In-Memory NoSQL Landscape (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the fundamental design principles for exploiting RDMAs in modern NoSQL systems. |
M. Hemmatpour; B. Montrucchio; M. Rebaudengo; M. Sadoghi; |
| 238 | LogStore: A Workload-aware, Adaptable Key-Value Store on Hybrid Storage Systems (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose our new key-value store, Log-Store, optimized for hybrid storage architectures. |
P. Menon; T. M. Qadah; T. Rabl; M. Sadoghi; H. -A. Jacobsen; |
| 239 | Entity Alignment for Knowledge Graphs with Multi-order Convolutional Networks (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an end-to-end, unsupervised entity alignment framework for cross-lingual KGs using multi-order graph convolutional networks. |
N. T. Tam; et al. |
| 240 | Compressed Indexes for Fast Search of Semantic Data (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a trie-based index layout to solve the problem and introduce two novel techniques to reduce its space of representation for improved effectiveness. |
R. Perego; G. E. Pibiri; R. Venturini; |
| 241 | FastDTW Is Approximate and Generally Slower Than The Algorithm It Approximates (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we make a surprising claim. In any realistic data mining application, the approximate FastDTW is much slower than the exact DTW. |
R. Wu; E. J. Keogh; |
| 242 | ESA-Stream: Efficient Self-Adaptive Online Data Stream Clustering (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As data streams are data-intensive, temporally ordered, and rapidly evolving, efficiently and effectively online clustering of data streams presents a challenging problem [1]. |
Y. Li; H. Li; Z. Wang; B. Liu; J. Cui; H. Fei; |
| 243 | CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an efficient GPU-training framework for the large-scale wide models, named cuWide. |
X. Miao; et al. |
| 244 | Reliability Maximization in Uncertain Graphs (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the novel and fundamental problem of adding a small number of edges in the uncertain network for maximizing the reliability between a given pair of nodes. |
X. Ke; A. Khan; M. Al Hasan; R. Rezvansangsari; |
| 245 | MaxiZone: Maximizing Influence Zone Over Geo-Textual Data (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the MaxiZone problem, we propose three algorithms, including a basic algorithm, an index-centric algorithm together with a series of optimizations and a sampling-based algorithm. |
Q. Liu; Z. Zhu; J. Xu; Y. Gao; |
| 246 | Efficient Shapelet Discovery for Time Series Classification (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel efficient shapelet discovery method, called BSPCOVER, to discover a set of high-quality shapelet candidates for model building. |
G. Li; B. Choi; J. Xu; S. S. Bhowmick; K. -P. Chun; G. L. H. Wong; |
| 247 | A Generic Ontology Framework for Indexing Keyword Search on Massive Graphs (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a generic ontology-based indexing framework for keyword search, called Bisimulation of Generalized Graph Index (BiG-index), to enhance the search performance. |
J. Jiang; B. Choi; J. Xu; S. S. Bhowmick; |
| 248 | LShape Partitioning: Parallel Skyline Query Processing Using MapReduce (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose two parallel skyline processing algorithms using a novel LShape partitioning strategy and an effective Propagation Filtering method. |
H. Wijayanto; W. Wang; W. -S. Ku; A. L. P. Chen; |
| 249 | Index-based Solutions for Efficient Density Peak Clustering (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, our focal point will be Density Peak Clustering (DPC) [1] , a popular approach towards obtaining density-based clusters. |
Z. Rasool; R. Zhou; L. Chen; C. Liu; J. Xu; |
| 250 | A Hybrid Data Cleaning Framework Using Markov Logic Networks (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel hybrid data cleaning framework, termed as MLNClean, which is capable of learning instantiated rules to supplement the insufficient integrity constraints. |
C. Ge; Y. Gao; X. Miao; B. Yao; H. Wang; |
| 251 | Truss-based Structural Diversity Search in Large Graphs (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a truss-based structural diversity model to address the limitations. |
J. Huang; X. Huang; J. Xu; |
| 252 | Towards Query Pricing on Incomplete Data (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore the pricing problem for queries over incomplete data. |
X. Miao; Y. Gao; L. Chen; H. Peng; J. Yin; Q. Li; |
| 253 | Effective Keyword Search in Weighted Graphs (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose and experimentally evaluate algorithms that optimize these objectives with an approximation ratio of two. |
M. Kargar; L. Golab; D. Srivastava; J. Szlichta; M. Zihayat; |
| 254 | Distributed Density Peaks Clustering Revisited (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a fast distributed density peaks clustering algorithm, FDDP, based on the z-value index. |
J. Lu; Y. Zhao; K. -L. Tan; Z. Wang; |
| 255 | Discovering Relaxed Functional Dependencies Based on Multi-attribute Dominance [Extended Abstract] Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The RFD discovery algorithm presented in this paper exploits the concept of dominance to automatically derive similarity thresholds. |
L. Caruccio; V. Deufemia; F. Naumann; G. Polese; |
| 256 | Constrained Truth Discovery (Extended Abstract) Related Papers Related Patents Related Grants Related Orgs Related Experts Details Abstract: Aggregating the information provided by multiple data sources, which is also known as information integration , plays an important role in data analytics. Since there often exists … |
C. Ye; et al. |
| 257 | Fairness in Rankings and Recommenders: Models, Methods and Research Directions Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our objectives are three-fold: (a) to provide a solid framework on a novel, quickly evolving, and impactful domain, (b) to present related methods and put them into perspective, and (c) to highlight challenges and research paths for researchers and practitioners that work in data management and applications. |
E. Pitoura; K. Stefanidis; G. Koutrika; |
| 258 | Countering Bias in Personalized Rankings : From Data Engineering to Algorithm Development Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This tutorial presents recent advances on the assessment and mitigation of data and algorithmic bias in personalized rankings. |
L. Boratto; M. Marras; |
| 259 | Workload-Aware Performance Tuning for Autonomous DBMSs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this tutorial, we focus on autonomous workload-aware performance tuning, which is expected to automatically and continuously tune the configuration as the workload changes. |
Z. Yan; J. Lu; N. Chainani; C. Lin; |
| 260 | High-Dimensional Similarity Search for Scalable Data Science Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this tutorial, we revisit the similarity search problem in light of the recent advances in the field and the new big data landscape. |
K. Echihabi; K. Zoumpatianos; T. Palpanas; |
| 261 | Evaluation of Duplicate Detection Algorithms: From Quality Measures to Test Data Generation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this tutorial, we present common methods to evaluate duplicate detection algorithms and to generate labeled test data. |
F. Panse; F. Naumann; |
| 262 | Nullius in Verba: Reproducibility for Database Systems Research, Revisited Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This tutorial revisits reproducible engineering in the face of state-of-the-art technology, and best practices gained in other computer science research communities. |
W. Mauerer; S. Scherzinger; |
| 263 | Exploratory Data Analysis in SAP IQ Using Query-Time Sampling Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we describe our early work on extending SAP IQ (a disk-based columnar RDBMS) to support approximate query processing for exploratory data analysis using a technique known as query-time sampling. |
X. Meng; G. Alu�; |
| 264 | Swift: Reliable and Low-Latency Data Processing at Cloud Scale Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper reports our experience with Swift, a system capable of efficiently running real-time and interactive data processing jobs at cloud scale. |
B. Wang; et al. |
| 265 | DBSpinner: Making A Case for Iterative Processing in Databases Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work1, we demonstrate how iterative CTEs can be efficiently incorporated into a production RDBMS without major intrusion to the system. |
S. Floratos; A. Ghazal; J. Sun; J. Chen; X. Zhang; |
| 266 | Prefix-Graph: A Versatile Log Parsing Approach Merging Prefix Tree with Probabilistic Graph Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Prefix-Graph, an online versatile log parsing approach. |
G. Chu; J. Wang; Q. Qi; H. Sun; S. Tao; J. Liao; |
| 267 | Microlearner: A Fine-grained Learning Optimizer for Big Data Workloads at Microsoft Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we describe building a learning query optimizer for big data workloads at Microsoft. |
A. Jindal; S. Qiao; R. Sen; H. Patel; |
| 268 | Query Rewriting Via Cycle-Consistent Translation for E-Commerce Search Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel deep neural network based approach to query rewriting, in order to tackle this problem. |
Y. Qiu; et al. |
| 269 | Learnings from A Retail Recommendation System on Billions of Interactions at Bol.com Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We discuss the design of a large-scale recommender system handling billions of interactions on a European e-commerce platform. |
B. Kersbergen; S. Schelter; |
| 270 | Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we leverage the Mixture of Expert (MoE) framework to learn a ranking model that specializes for each query category. |
Z. Xiao; et al. |
| 271 | Explore User Neighborhood for Real-time E-commerce Recommendation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome this challenge, we propose a framework called self-complementary collaborative filtering (SCCF) which can make recommendations with both global and local information in real time. |
X. Xie; et al. |
| 272 | Billion-scale Pre-trained E-commerce Product Knowledge Graph Model Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, to avoid this problem, we propose a Pre-trained Knowledge Graph Model (PKGM) for our billion-scale e-commerce product knowledge graph, providing item knowledge services in a uniform way for embedding-based models without accessing triple data in the knowledge graph. |
W. Zhang; C. -M. Wong; G. Ye; B. Wen; W. Zhang; H. Chen; |
| 273 | Purchase Intent Forecasting with Convolutional Hierarchical Transformer Networks Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this challenge, we develop a Convolutional Hierarchical TRansformer networks (CHTR), to enable the purchase pattern modeling with the multi-grained temporal dynamics, so as to alleviate the data imbalance issue. |
C. Huang; J. Zhao; D. Yin; |
| 274 | ATNN: Adversarial Two-Tower Neural Network for New Item�s Popularity Prediction in E-commerce Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle these challenges, we propose a novel Adversarial Two-tower Neural Network (ATNN) model for new arrivals CTR predictions by introducing an adversarial network to a two-tower network. |
S. Xin; et al. |
| 275 | Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a data-driven approach, Spatial-Temporal Aided Double Deep Graph Network (ST-DDGN), to solve industry-scale DPDP. |
X. Li; et al. |
| 276 | The IoT Meta-Control Firewall Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present an innovative system, coined IoT Meta-Control Firewall (IMCF), which internally deploys an AI-inspired Energy-Planner (EP) algorithm that exploits domain-specific operators to balance the trade-off between convenience and energy consumption in satisfying the RAW pipelines of users. |
S. Constantinou; A. Konstantinidis; D. Zeinalipour-Yazti; P. K. Chrysanthis; |
| 277 | GeoDart: A System for Discovering Maps Discrepancies Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a system, named GeoDart, that compares publicly available routing data from the APIs of Bing Maps, Google Maps, and OpenStreetMaps (OSM) to automatically discover discrepancies. |
A. Bandil; et al. |
| 278 | Implementing Rigid Temporal Geometries in Moving Object Databases Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to provide an implementation of rigid temporal geometries into MobilityDB, an open-source moving object database, that extends PostgreSQL and PostGIS. |
M. Schoemans; M. Sakr; E. Zim�nyi; |
| 279 | IntelliTag: An Intelligent Cloud Customer Service System Based on Tag Recommendation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To reduce the customer service pressure of small and medium-sized enterprises, we propose an intelligent cloud customer service system, called IntelliTag. |
M. Yang; et al. |
| 280 | IPS: Unified Profile Management for Ubiquitous Online Recommendations Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce Instance Profile Service (IPS), a large scale distributed system for managing unstructured profile data as well as serving various feature computations at ByteDance. |
R. Shi; et al. |
| 281 | Turbo: Fraud Detection in Deposit-free Leasing Service Via Real-Time Behavior Network Mining Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we contribute Turbo, an efficient graph-based anti-fraud system, to fully exploit the abundant user behavior logs in a real-time manner. |
S. Hu; et al. |
| 282 | Large-scale Fake Click Detection for E-commerce Recommendation Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we carried out pioneering work in analyzing and summarizing the characteristics of the false click information produced by attackers on the target products in the Ride Item’s Coattails attack and designed a set of attack detection techniques suitable for e-commerce recommendation systems. |
J. Li; et al. |
| 283 | Improving Conversational Recommender System By Pretraining Billion-scale Knowledge Graph Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we propose a novel knowledge-enhanced deep cross network (K-DCN), a two-step (pretrain and fine-tune) CTR prediction model to recommend items. |
C. -M. Wong; et al. |
| 284 | Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To resolve this, we propose a new structure learning algorithm LEAST, which comprehensively fulfills our business requirements as it attains high accuracy, efficiency and scalability at the same time. |
R. Zhu; et al. |
| 285 | ReLink: Complete-Link Industrial Record Linkage Over Hybrid Feature Spaces Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Through our proposed system ‘ReLink’, we carefully mitigate these challenges and demonstrate that it not only significantly outperforms SOTA baselines on industrial datasets but also on majority of research benchmarks. |
S. R. Joshi; A. Somani; S. Roy; |
| 286 | Distributed Company Control in Company Shareholding Graphs Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper is based on our experience with the Central Bank of Italy and presents an approach to the solution of the company control problem in distributed settings, especially relevant, as large and distributed ownership graphs reflect European-size applications where scalability is paramount.In particular, we formalize the problem as query answering on a large distributed database. |
A. Gulino; S. Ceri; G. Gottlob; E. Sallinger; L. Bellomarini; |
| 287 | SPARQLIt: Interactive SPARQL Query Refinement Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose to demonstrate an interactive system called SPARQLIt, assisting users in the formulation of SPARQL queries. |
Y. Amsterdamer; Y. Callen; |
| 288 | SubDEx: Exploring Ratings in Subjective Databases Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We demonstrate SubDEx, a dedicated framework for Subjective Data Exploration (SDE). |
S. Amer-Yahia; T. Milo; B. Youngmann; |
| 289 | SOUP: A Fleet Management System for Passenger Demand Prediction and Competitive Taxi Supply Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We demonstrate a fleet management system called SOUP that aims at minimizing taxi idle time and that monitors the fleet movement status. |
Q. Hu; L. Ming; R. Xi; L. Chen; C. S. Jensen; B. Zheng; |
| 290 | VADETIS: An Explainable Evaluator for Anomaly Detection Techniques Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this demo, we present a new evaluator that allows to peruse the performance of several anomaly detection techniques and supports practitioners in understanding the behavior and (dis-)advantages of each technique for a given dataset. |
A. Khelifati; M. Khayati; P. Cudr�-Mauroux; A. H�nni; Q. Liu; M. Hauswirth; |
| 291 | CoWiz: Interactive Covid-19 Visualization Based On Multilayer Network Analysis Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper elaborates on the types of analysis, underlying model, and how a flexible visualization dashboard has been developed using open source software and data sets. |
K. Samant; E. Memeti; A. Santra; E. Karim; S. Chakravarthy; |
| 292 | SpeakNav: A Voice-based Navigation System Via Route Description Language Understanding Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the SpearkNav navigation system that enables users to describe intended routes via speech and supports clue-based route retrieval. |
L. Bi; J. Cao; G. Li; N. Q. Viet Hung; C. S. Jensen; B. Zheng; |
| 293 | QeNoBi: A System for QuErying and Mining BehavIoral Patterns Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We demonstrate QeNoBi, a system for mining and querying customer behavioral patterns. |
A. Chibah; S. Amer-Yahia; L. Berti-Equille; |
| 294 | CREATe: Clinical Report Extraction and Annotation Technology Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel computational resource platform, CREATe, for extracting, indexing, and querying the contents of clinical case reports. |
Y. Zhou; et al. |
| 295 | UniKG: A Unified Interoperable Knowledge Graph Database System Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this demonstration, we propose a unified interoperable knowledge graph database system, UniKG. |
B. Liu; X. Wang; P. Liu; S. Li; Q. Fu; Y. Chai; |
| 296 | A Cockpit for The Development and Evaluation of Autonomous Database Systems Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The presented cockpit enables an interactive assessment of the impact of autonomous components for database systems by comparing (autonomous) systems with different configurations side by side. |
J. Kossmann; et al. |
| 297 | Automated Data Science for Relational Data Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we demonstrate a novel system called OneBM (One Button Machine), that enables data scientists to increase their efficiency with automated feature engineering for relational data. |
H. T. Lam; et al. |
| 298 | Josch: Managing Schemas for NoSQL Document Stores Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this tool demo, we present Josch, which integrates state-ofthe-art third-party tools to support novel workflows for NoSQL document stores: Using Josch, DevOps teams may (1) extract a JSON Schema declaration from the production data instance, (2) manually refactor the schema (e.g., to account for upcoming schema changes), and (3) compare the extracted and the refactored schema, on a semantic level, e.g., to ensure that the rewritten schema is a generalization. |
M. Fruth; K. Dauberschmidt; S. Scherzinger; |
| 299 | DeBinelle: Semantic Patches for Coupled Database-Application Evolution Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce DeBinelle, a novel framework and domain-specific language for semantic patches that abstracts DB-variant schema changes and coupled program code into a single, unified representation. |
S. Scherzinger; W. Mauerer; H. Kondylakis; |
| 300 | ConCaT: Construction of Category Trees from Search Queries in E-Commerce Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To support a browsing experience that better matches the user information needs, and to considerably reduce the manual work performed by taxonomists, we propose CONCAT – a system that leverages the demand-based nature of the query paradigm to automatically build a category tree that is maximally similar to the result sets for search queries. |
U. Avron; S. Gershtein; I. Guy; T. Milo; S. Novgorodov; |
| 301 | A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap, we build ThreatRaptor, a system that facilitates cyber threat hunting in computer systems using OSCTI. |
P. Gao; et al. |
| 302 | Odlaw: A Tool for Retroactive GDPR Compliance Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this demo, we present ODLAW, a new tool for retroactive compliance with privacy laws like the European Union?s General Data Protection Regulation (GDPR). |
C. Luckett; A. Crotty; A. Galakatos; U. Cetintemel; |
| 303 | PITA: Privacy Through Provenance Abstraction Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose to demonstrate PITA, a system designed to allow the release of provenance information, while hiding the properties of the underlying query. |
D. Deutch; A. Frankenthal; A. Gilad; Y. Moskovitch; |
| 304 | The F4U System for Understanding The Effects of Data Quality Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We demonstrate a system that enables a data-centric approach in understanding data quality. |
D. Foroni; M. Lissandrini; Y. Velegrakis; |
| 305 | FloraVision: A Spatial Crowd-based Learning System for California Native Plants Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To showcase this class of applications, we present FloraVision, an end-to-end system that integrates ML, crowdsourcing, and EC to automate the detection, mapping, and exploration of California Native Plants. |
G. Constantinou; et al. |
| 306 | Clouseau: Blockchain-based Data Integrity for HDFS Clusters Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As a remedy, we present Clouseau, a blockchain-based system that provides verifiable integrity over HDFS, while it does not incur significant overhead at the critical path of read/write operations. |
A. Konsta; I. Mytilinis; K. Doka; S. Niarchos; N. Koziris; |
| 307 | REACT: Real-Time Contact Tracing and Risk Monitoring Via Privacy-Enhanced Mobile Tracking Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrate the procedure of contact tracing using our application and the utility of contact tracing given the protected locations. |
Y. Da; R. Ahuja; L. Xiong; C. Shahabi; |
| 308 | Edge Sparsification for Graphs Via Meta-Learning Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel edge sparsification approach for semi-supervised learning on undirected and attributed graphs. |
G. Wan; H. Schweitzer; |
| 309 | MoniLog: An Automated Log-Based Anomaly Detection System for Cloud Computing Infrastructures Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we will introduce MoniLog, a distributed approach to detect real-time anomalies within large-scale environments. |
A. Vervaet; |
| 310 | Graph Based Approach to Real-Time Metro Passenger Flow Anomaly Detection Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel abnormal passenger flow detection method based on smart card data. |
W. Zhang; |
| 311 | Combining Anatomical Constraints and Deep Learning for 3-D CBCT Dental Image Multi-label Segmentation Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: For non-separable constraints, we propose to combine the importance sampling based approach and the stochastic optimization algorithm. |
J. Huang; H. Yan; J. Li; H. M. Stewart; F. Setzer; |
| 312 | Tensor Topic Models with Graphs and Applications on Individualized Travel Patterns Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle these challenges, we proposed two novel frameworks based on topic models with the external information incorporated as graphs: Trips and passengers are formulated as tensor words and tensor documents to preserve data nature; To learn multiclustering, we proposed a graph-regularized tensor Latent Dirichlet Allocation model, with graph structure formulated as Laplacian penalty; To learn passenger clustering, we proposed a graph-based tensor Dirich-let Multinomial Mixture model with graph Laplacian penalty and l1-norm penalty for cluster amount autodetermination. |
Z. LI; |
| 313 | BERT-based Dynamic Clustering of Subway Stations Using Flow Information Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a BERT-based feature extraction framework to capture dynamic mobility patterns for metro stations time to time. |
M. Li; |