Paper Digest: SIGIR 2013 Highlights

July 28, 2013June 26, 2020 admin

SIGIR (Annual International ACM SIGIR Conference on Research and Development in Information Retrieval) is one of the top information retrieval conferences in the world.

To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper. Readers are encouraged to read these machine generated highlights / summaries to quickly get the main idea of each paper.

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TABLE 1: SIGIR 2013 Papers

	Title	Authors	Highlight
1	Riding the multimedia big data wave	John R. Smith	In this talk we present a perspective across multiple industry problems, including safety and security, medical, Web, social and mobile media, and motivate the need for large-scale analysis and retrieval of multimedia data.
2	Beliefs and biases in web search	Ryen White	In this paper we study search-related biases via multiple probes: an exploratory retrospective survey, human labeling of the captions and results returned by a Web search engine, and a large-scale log analysis of search behavior on that engine.
3	Improving search result summaries by using searcher behavior data	Mikhail Ageev, Dmitry Lagun, Eugene Agichtein	We present a new approach to improving result summaries by incorporating post-click searcher behavior data, such as mouse cursor movements and scrolling over the result documents.
4	How query cost affects search behavior	Leif Azzopardi, Diane Kelly, Kathy Brennan	A between-subjects laboratory study with 36 undergraduate subjects was conducted, where subjects were randomly assigned to use one of three search interfaces that varied according to the amount of physical cost required to query: Structured (high cost), Standard (medium cost) and Query Suggestion (low cost).
5	Search engine switching detection based on user personal preferences and behavior patterns	Denis Savenkov, Dmitry Lagun, Qiaoling Liu	In this paper we study the effectiveness of learning personal behavior patterns for switching detection and present a personalized approach which uses user’s session history containing sessions with and without switches.
6	Emerging topic detection for organizations from microblogs	Yan Chen, Hadi Amiri, Zhoujun Li, Tat-Seng Chua	Emerging topic detection for organizations from microblogs
7	Pseudo test collections for training and tuning microblog rankers	Richard Berendsen, Manos Tsagkias, Wouter Weerkamp, Maarten de Rijke	We describe a method for generating queries and relevance judgments for microblog search in an unsupervised way.
8	Learning latent friendship propagation networks with interest awareness for link prediction	Jun Zhang, Chaokun Wang, Philip S. Yu, Jianmin Wang	In this paper, we try to adopt this sociological principle to explain the evolution of networks and study the latent friendship propagation.
9	An experimental study on implicit social recommendation	Hao Ma	In this paper, we study the following two research problems: (1) In some systems without explicit social information, can we still improve recommender systems using implicit social information?
10	Task-aware query recommendation	Henry Feild, James Allan	To minimize the impact of off-task queries on recommendation performance, we consider automatic methods of identifying such queries using a state of the art search task identification technique.
11	Extracting query facets from search results	Weize Kong, James Allan	We propose two algorithms for approximate inference on the graphical model since exact inference is intractable.
12	Learning to personalize query auto-completion	Milad Shokouhi	In this paper, we present a supervised framework for personalizing auto-completion ranking.
13	Leveraging conceptual lexicon: query disambiguation using proximity information for patent retrieval	Parvaz Mahdabi, Shima Gerani, Jimmy Xiangji Huang, Fabio Crestani	Patent prior art search is a task in patent retrieval where the goal is to rank documents which describe prior art work related to a patent application.
14	Aggregated search interface preferences in multi-session search tasks	Marc Bron, Jasmijn van Gorp, Frank Nack, Lotte Belice Baltussen, Maarten de Rijke	In the longitudinal study we follow the use of tabbed and blended displays by 25 students during a project.
15	An effective implicit relevance feedback technique using affective, physiological and behavioural features	Yashar Moshfeghi, Joemon M. Jose	This paper investigates whether affective and physiological signals can be used as a complementary source of information for behavioural signals (i.e. dwell time) to create a reliable signal for relevance judgement prediction.
16	How do users respond to voice input errors?: lexical and phonetic query reformulation in voice search	Jiepu Jiang, Wei Jeng, Daqing He	We conducted user experiments with native English speakers on their query reformulation behaviors in voice search and found that users often reformulate queries with both lexical and phonetic changes to previous queries.
17	Mining touch interaction data on mobile devices to predict web search result relevance	Qi Guo, Haojian Jin, Dmitry Lagun, Shuai Yuan, Eugene Agichtein	In this paper, we present, to our knowledge, the first in-depth study of modeling interactions on touch-enabled device for improving Web search ranking.
18	An information-theoretic account of static index pruning	Ruey-Cheng Chen, Chia-Jung Lee	In this paper, we recast static index pruning as a model induction problem under the framework of Kullback’s principle of minimum cross-entropy.
19	Document identifier reassignment and run-length-compressed inverted indexes for improved search performance	Diego Arroyuelo, Senén González, Mauricio Oyarzún, Victor Sepulveda	In this paper we follow this line of research, yet from a different perspective.
20	Fast document-at-a-time query processing using two-tier indexes	Cristian Rossi, Edleno S. de Moura, Andre L. Carvalho, Altigran S. da Silva	In this paper we present two new algorithms designed to reduce the overall time required to process top-k queries.
21	Faster and smaller inverted indices with treaps	Roberto Konow, Gonzalo Navarro, Charles L.A. Clarke, Alejandro López-Ortíz	We introduce a new representation of the inverted index that performs faster ranked unions and intersections while using less space.
22	An unsupervised topic segmentation model incorporating word order	Shoaib Jameel, Wai Lam	We present a new unsupervised topic discovery model for a collection of text documents.
23	Semantic hashing using tags and topic modeling	Qifan Wang, Dan Zhang, Luo Si	This paper proposes a novel hashing approach, Semantic Hashing using Tags and Topic Modeling (SHTTM), to incorporate both the tag information and the similarity information from probabilistic topic modeling.
24	Incorporating popularity in topic models for social network analysis	Youngchul Cha, Bin Bi, Chu-Cheng Hsieh, Junghoo Cho	Topic models are used to group words in a text dataset into a set of relevant topics.
25	Topic hierarchy construction for the organization of multi-source user generated contents	Xingwei Zhu, Zhao-Yan Ming, Xiaoyan Zhu, Tat-Seng Chua	In this research, we propose a framework to organize information from multiple UGC sources by a topic hierarchy which is automatically generated and updated using the UGCs.
26	Looking ahead: query preview in exploratory search	Pernilla Qvarfordt, Gene Golovchinsky, Tony Dunnigan, Elena Agapie	Exploratory search is a complex, iterative information seeking activity that involves running multiple queries and finding and examining many documents.
27	News vertical search: when and what to display to users	Richard McCreadie, Craig Macdonald, Iadh Ounis	In this paper, we investigate to what extent real-time content from newswire, blogs, Twitter and Wikipedia sources are useful to return to the user in the current fast-paced news search setting.
28	Toward self-correcting search engines: using underperforming queries to improve search	Ahmed Hassan, Ryen W. White, Yi-Min Wang	In this paper, we present a method for automatically identifying poorly-performing query groups where a search engine may not meet searcher needs.
29	Fighting search engine amnesia: reranking repeated results	Milad Shokouhi, Ryen W. White, Paul Bennett, Filip Radlinski	Web search engines frequently show the same documents repeatedly for different queries within the same search session, in essence forgetting when the same documents were already shown to users.
30	Addressing cold-start in app recommendation: latent user models constructed from twitter followers	Jovian Lin, Kazunari Sugiyama, Min-Yen Kan, Tat-Seng Chua	In this paper, we describe a method that accounts for nascent information culled from Twitter to provide relevant recommendation in such cold-start situations.
31	A location-based news article recommendation with explicit localized semantic analysis	Jeong-Woo Son, A-Yeong Kim, Seong-Bae Park	This paper proposes a novel news article recommendation that reflects the geographical context of the user.
32	Opportunity model for e-commerce recommendation: right product; right time	Jian Wang, Yi Zhang	We adapt the proportional hazards modeling approach in survival analysis to the recommendation research field and propose a new opportunity model to explicitly incorporate time in an e-commerce recommender system.
33	Improve collaborative filtering through bordered block diagonal form matrices	Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma	This paper presents a novel and general collaborative filtering framework based on (Approximate) Bordered Block Diagonal Form structure of user-item rating matrices.
34	Personalized ranking model adaptation for web search	Hongning Wang, Xiaodong He, Ming-Wei Chang, Yang Song, Ryen W. White, Wei Chu	In this paper, we propose a general ranking model adaptation framework for personalized search.
35	Ranking document clusters using markov random fields	Fiana Raiber, Oren Kurland	We present a novel cluster ranking approach that utilizes Markov Random Fields (MRFs).
36	A novel TF-IDF weighting scheme for effective ranking	Jiaul H. Paik	This article proposes a novel TF-IDF term weighting scheme that employs two different within document term frequency normalizations to capture two different aspects of term saliency.
37	Retrieving documents with mathematical content	Shahab Kamali, Frank Wm. Tompa	In this paper we study the fundamental and challenging problems in mathematics retrieval, that is how to capture the relevance of mathematical expressions, how to query them, and how to evaluate the results.
38	Time-aware point-of-interest recommendation	Quan Yuan, Gao Cong, Zongyang Ma, Aixin Sun, Nadia Magnenat- Thalmann	In this paper, we define a new problem, namely, the time-aware POI recommendation, to recommend POIs for a given user at a specified time in a day.
39	Modeling user’s receptiveness over time for recommendation	Wei Chen, Wynne Hsu, Mong Li Lee	In this paper, we propose a probabilistic generative model, called Receptiveness over Time Model (RTM), to capture this interaction.
40	Query representation for cross-temporal information retrieval	Miles Efron	We focus on ways to combine evidence to improve CTIR effectiveness, proposing and testing several ways to handle language change during book search.
41	On the measurement of test collection reliability	Julián Urbano, Mónica Marrero, Diego Martín	Generalizability Theory was proposed as an alternative founded on analysis of variance that provides reliability indicators based on statistical theory.
42	Deciding on an adjustment for multiplicity in IR experiments	Leonid Boytsov, Anna Belova, Peter Westfall	We evaluate statistical inference procedures for small-scale IR experiments that involve multiple comparisons against the baseline.
43	Preference based evaluation measures for novelty and diversity	Praveen Chandar, Ben Carterette	In this work, we propose an evaluation framework that not only can consider implicit factors but also handles differences in user preference due to varying underlying information need.
44	Competence-based song recommendation	Lidan Shou, Kuang Mao, Xinyuan Luo, Ke Chen, Gang Chen, Tianlei Hu	In this paper, we propose a novel singing competence-based song recommendation framework.
45	A low rank structural large margin method for cross-modal ranking	Xinyan Lu, Fei Wu, Siliang Tang, Zhongfei Zhang, Xiaofei He, Yueting Zhuang	In this paper, we consider this problem from a new perspective as a listwise ranking problem and propose a general cross-modal ranking algorithm to optimize the listwise ranking loss with a low rank embedding, which we call Latent Semantic Cross-Modal Ranking (LSCMR).
46	Learning to name faces: a multimodal learning scheme for search-based face annotation	Dayong Wang, Steven C.H. Hoi, Pengcheng Wu, Jianke Zhu, Ying He, Chunyan Miao	In this paper, we tackle this open problem by investigating a search-based face annotation (SBFA) paradigm for mining large amounts of web facial images freely available on the WWW.
47	Utilizing query change for session search	Dongyi Guan, Sicong Zhang, Hui Yang	We propose to model session search as a Markov Decision Process (MDP).
48	Toward whole-session relevance: exploring intrinsic diversity in web search	Karthik Raman, Paul N. Bennett, Kevyn Collins-Thompson	Toward optimizing whole-session or task relevance, we characterize and address the problem of intrinsic diversity (ID) in retrieval [30], a type of complex task that requires multiple interactions with current search engines.
49	Summaries, ranked retrieval and sessions: a unified framework for information access evaluation	Tetsuya Sakai, Zhicheng Dou	We introduce a general information access evaluation framework that can potentially handle summaries, ranked document lists and even multi query sessions seamlessly.
50	Modeling click-through based word-pairs for web search	Jagadeesh Jagarlamudi, Jianfeng Gao	This paper presents two document ranking models that combine the strengths of both the approaches by explicitly modeling word-pairs.
51	Click model-based information retrieval metrics	Aleksandr Chuklin, Pavel Serdyukov, Maarten de Rijke	In this paper we bring these two directions together and propose a common approach to converting any click model into an evaluation metric.
52	Incorporating vertical results into search click models	Chao Wang, Yiqun Liu, Min Zhang, Shaoping Ma, Meihong Zheng, Jing Qian, Kuo Zhang	According these analysis, we found that different result appearances may cause different behavior biases both for vertical results (local effect) and for the whole result lists (global effect). With the help of a popular commercial search engine in China, we collected a large scale log data set which contains behavior information on both vertical and ordinary results.
53	Personalized time-aware tweets summarization	Zhaochun Ren, Shangsong Liang, Edgar Meij, Maarten de Rijke	We propose a time-aware user behavior model, the Tweet Propagation Model (TPM), in which we infer dynamic probabilistic distributions over interests and topics.
54	Exploiting hybrid contexts for Tweet segmentation	Chenliang Li, Aixin Sun, Jianshu Weng, Qi He	In this paper, we propose a novel framework for tweet segmentation in a batch mode, called HybridSeg.
55	Sumblr: continuous summarization of evolving tweet streams	Lidan Shou, Zhenhua Wang, Ke Chen, Gang Chen	In this paper, we study continuous tweet summarization as a solution to address this problem.
56	Exploiting user feedback to learn to rank answers in q&a forums: a case study with stack overflow	Daniel Hasan Dalip, Marcos André Gonçalves, Marco Cristo, Pavel Calado	To tackle with this problem, we propose a learning to rank (L2R) approach for ranking answers in Q&A forums.
57	An incremental approach to efficient pseudo-relevance feedback	Hao Wu, Hui Fang	In this paper, we study how to improve the efficiency of pseudo-relevance feedback methods.
58	Query expansion using path-constrained random walks	Jianfeng Gao, Gu Xu, Jinxi Xu	This paper exploits Web search logs for query expansion (QE) by presenting a new QE method based on path-constrained random walks (PCRW), where the search logs are represented as a labeled, directed graph, and the probability of picking an expansion term for an input query is computed by a learned combination of constrained random walks on the graph.
59	Efficient query construction for large scale data	Elena Demidova, Xuan Zhou, Wolfgang Nejdl	This paper presents a set of techniques to boost the scalability of interactive query construction, from the perspective of both, user interaction cost and performance.
60	Compact query term selection using topically related text	K. Tamsin Maxwell, W. Bruce Croft	In this paper, we present a novel term ranking algorithm, PhRank, that extends work on Markov chain frameworks for query expansion to select compact and focused terms from within a query itself.
61	Sentiment diversification with different biases	Elif Aktolga, James Allan	In this paper, we diversify with sentiments according to an explicit bias.
62	Term level search result diversification	Van Dang, Bruce W. Croft	This paper introduces a new approach: term-level diversification.
63	Search result diversification in resource selection for federated search	Dzung Hong, Luo Si	This paper proposes two general approaches to model both result relevance and diversification in selecting sources, in order to provide more comprehensive coverage of multiple aspects of a user query. We propose a set of new metrics for resource selection in federated search to evaluate the diversification performance of different approaches.
64	The effect of threshold priming and need for cognition on relevance calibration and assessment	Falk Scholer, Diane Kelly, Wan-Ching Wu, Hanseul S. Lee, William Webber	Showing documents to assessors in different orderings, however, may lead to different assessment outcomes.
65	User model-based metrics for offline query suggestion evaluation	Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis	Inspired by the cascade user models and state-of-the-art evaluation metrics in the web search domain, we address the query suggestion evaluation, by first studying the users behaviour from a search engine’s query log and thereby deriving a new family of user models describing the users interaction with a query suggestion mechanism.
66	A general evaluation measure for document organization tasks	Enrique Amigó, Julio Gonzalo, Felisa Verdejo	In this paper we propose two complementary evaluation measures — Reliability and Sensitivity — for the generic Document Organization task which are derived from a proposed set of formal constraints (properties that any suitable measure must satisfy).
67	Modeling term dependencies with quantum language models for IR	Alessandro Sordoni, Jian-Yun Nie, Yoshua Bengio	Recently, Quantum Theory (QT) has been proposed as a possible, more general framework for IR.
68	Copulas for information retrieval	Carsten Eickhoff, Arjen P. de Vries, Kevyn Collins-Thompson	To address these issues, we introduce the use of copulas, a powerful statistical framework for modeling complex multi-dimensional dependencies, to information retrieval tasks.
69	Taily: shard selection using the tail of score distributions	Robin Aly, Djoerd Hiemstra, Thomas Demeester	This paper proposes Taily, a novel shard selection algorithm that models a query’s score distribution in each shard as a Gamma distribution and selects shards with highly scored documents in the tail of the distribution.
70	A mutual information-based framework for the analysis of information retrieval systems	Peter B. Golbus, Javed A. Aslam	We propose a probabilistic framework for evaluation which we use to develop new information-theoretic evaluation metrics.
71	The impact of solid state drive on search engine cache management	Jianguo Wang, Eric Lo, Man Lung Yiu, Jiancong Tong, Gang Wang, Xiaoguang Liu	In this paper, we carry out a series of empirical experiments to study the impact of SSD on search engine cache management.
72	Faster upper bounding of intersection sizes	Daisuke Takuma, Hiroki Yanagisawa	In this paper, we describe a new data structure, a Cardinality Filter, to quickly compute an upper bound on the size of a set intersection.
73	Cache-conscious performance optimization for similarity search	Maha Alabduljalil, Xun Tang, Tao Yang	This paper proposes a cache-conscious data layout and traversal optimization to reduce the execution time through size-controlled data splitting and vector coalescing.
74	A candidate filtering mechanism for fast top-k query processing on modern cpus	Constantinos Dimopoulos, Sergey Nepomnyachiy, Torsten Suel	In this paper, we propose a method for accelerating such top-k queries that builds on and generalizes methods recently proposed by several groups of researchers based on Block-Max Indexes.
75	A test collection for entity search in DBpedia	Krisztian Balog, Robert Neumayer	We develop and make publicly available an entity search test collection based on the DBpedia knowledge base.
76	Author disambiguation by hierarchical agglomerative clustering with adaptive stopping criterion	Lei Cen, Eduard C. Dragut, Luo Si, Mourad Ouzzani	This paper proposes new research for entity disambiguation with the focus of name disambiguation in digital libraries.
77	Document features predicting assessor disagreement	Praveen Chandar, William Webber, Ben Carterette	In this paper we study the relationship between assessor disagreement and various topic independent factors such as readability and cohesiveness.
78	Exploring semi-automatic nugget extraction for Japanese one click access evaluation	Matthew Ekstrand-Abueg, Virgil Pavlu, Makoto Kato, Tetsuya Sakai, Takehiro Yamamoto, Mayu Iwata	We compare manually-extracted and semi-automatically-extracted Japanese nuggets to demonstrate the coverage and efficiency of the semi-automatic nugget extraction.
79	Report from the NTCIR-10 1CLICK-2 Japanese subtask: baselines, upperbounds and evaluation robustness	Makoto P. Kato, Tetsuya Sakai, Takehiro Yamamoto, Mayu Iwata	Using the official Japanese results of the second round of the 1CLICK task from NTCIR-10, we discuss our task setting and evaluation framework.
80	Building a web test collection using social media	Chia-Jung Lee, W. Bruce Croft	This paper describes a novel way of building a test collection for web search by exploiting the link information from this type of social media data.
81	Summary of the NTCIR-10 INTENT-2 task: subtopic mining and search result diversification	Tetsuya Sakai, Zhicheng Dou, Takehiro Yamamoto, Yiqun Liu, Min Zhang, Makoto P. Kato, Ruihua Song, Mayu Iwata	This paper summarises the novel features of the Second INTENT task at NTCIR-10 and its main findings, and poses some questions for future diversified search evaluation.
82	Is relevance hard work?: evaluating the effort of making relevant assessments	Robert Villa, Martin Halvey	The judging of relevance has been a subject of study in information retrieval for a long time, especially in the creation of relevance judgments for test collections. By better understanding this effort in isolation, we may provide data which can be used to create better models of search.
83	A weakly-supervised detection of entity central documents in a stream	Ludovic Bonnefoy, Vincent Bouvier, Patrice Bellot	We propose an approach which does not require new training data when processing a new entity.
84	Sentiment analysis of user comments for one-class collaborative filtering over ted talks	Nikolaos Pappas, Andrei Popescu-Belis	We propose a sentiment-aware nearest neighbor model (SANN) for multimedia recommendations over TED talks, which makes use of user comments.
85	Modeling the uniqueness of the user preferences for recommendation systems	Haggai Roitman, David Carmel, Yosi Mass, Iris Eiron	In this paper we propose a novel framework for modeling the uniqueness of the user preferences for recommendation systems.
86	Recommending personalized touristic sights using google places	Maya Sappelli, Suzan Verberne, Wessel Kraaij	In our content-based approach, we collected initial recommendations using the location context as search query in Google Places.
87	Optimizing top-n collaborative filtering via dynamic negative item sampling	Weinan Zhang, Tianqi Chen, Jun Wang, Yong Yu	In this paper, we propose to dynamically choose negative training samples from the ranked list produced by the current prediction model and iteratively update our model.
88	Towards retrieving relevant information graphics	Zhuo Li, Matthew Stagitis, Sandra Carberry, Kathleen F. McCoy	Our goal is to build a system for retrieving bar charts and line graphs that reasons about the content of the graphic itself in deciding its relevance to the user query.
89	Hybrid retrieval approaches to geospatial music recommendation	Markus Schedl, Dominik Schnitzer	In this paper, we propose hybrid music recommendation algorithms that combine information on the music content, the music context, and the user context, in particular, integrating location-aware weighting of similarities.
90	Leveraging viewer comments for mood classification of music video clips	Takehiro Yamamoto, Satoshi Nakamura	This short paper proposes a method to classify music video clips uploaded to a video sharing service into music mood categories such as ‘cheerful,’ ‘wistful,’ and ‘aggressive.’
91	Exploiting semantics for improving clinical information retrieval	Atanaz Babashzadeh, Jimmy Huang, Mariam Daoud	To address these issues, in this paper we attempt to use semantic information to improve the performance of clinical IR systems by representing queries in an expressive and meaningful context.
92	Interpretation of coordinations, compound generation, and result fusion for query variants	Johannes Leveling	We evaluate the approach on German standard IR benchmarking data.
93	Time-aware structured query suggestion	Taiki Miyanishi, Tetsuya Sakai	In this study, we propose Time-aware Structured Query Suggestion (TaSQS) which clusters query suggestions along a timeline so that the user can narrow down his search from a temporal point of view.
94	Flat vs. hierarchical phrase-based translation models for cross-language information retrieval	Ferhan Ture, Jimmy Lin	In this paper, we compare flat and hierarchical phrase-based translation models for query translation.
95	Here and there: goals, activities, and predictions about location from geotagged queries	Robert West, Ryen W. White, Eric Horvitz	We explore the links between users’ queries on mobile devices and their locations and movement, with a focus on interpreting queries about addresses.
96	Query change as relevance feedback in session search	Sicong Zhang, Dongyi Guan, Hui Yang	In this paper, we propose to use query change as a new form of relevance feedback for better session search.
97	Is uncertain logical-matching equivalent to conditional probability?	Karam Abdulahhad, Jean-Pierre Chevallet, Catherine Berrut	In this study, we revisit the Van Rijsbergen’s assumptions about: 1- the logical implication ->’ is not the material one, and 2- P(d->q) could be estimated by the conditional probability P(q\|d).
98	Boosting novelty for biomedical information retrieval through probabilistic latent semantic analysis	Xiangdong An, Jimmy Xiangji Huang	In this paper, we study how to boost novelty for biomedical information retrieval through probabilistic latent semantic analysis.
99	Learning to combine representations for medical records search	Nut Limsopatham, Craig Macdonald, Iadh Ounis	In this paper, we propose a novel learning framework that models the importance of the bag-of-words and the bag-of-concepts representations, combining their scores on a per-query basis.
100	Kinship contextualization: utilizing the preceding and following structural elements	Muhammad A. Norozi, Paavo Arvola	In this study we hypothesize that the context of an XML-element originated from its \textit{preceding} and \textit{following} elements in the sequential ordering of a document improves the quality of retrieval.
101	The cluster hypothesis for entity oriented search	Hadas Raviv, Oren Kurland, David Carmel	In this work we study the cluster hypothesis for entity oriented search (EOS).
102	Self reinforcement for important passage retrieval	Ricardo Ribeiro, Luís Marujo, David Martins de Matos, João P. Neto, Anatole Gershman, Jaime Carbonell	We present a new two-stage method that starts by extracting a collection of key phrases that will be used to help centrality-as-relevance retrieval model.
103	What can pictures tell us about web pages?: improving document search using images	Sergio Rodriguez-Vaamonde, Lorenzo Torresani, Andrew Fitzgibbon	In this paper we study whether the content of the pictures appearing in a Web page can be used to enrich the semantic description of an HTML document and consequently boost the performance of a keyword-based search engine.
104	Estimating query representativeness for query-performance prediction	Mor Sondak, Anna Shtok, Oren Kurland	We present a novel probabilistic framework for QPP that gives rise to an important aspect that was not addressed in previous work; namely, the extent to which the query effectively represents the information need for retrieval.
105	Interoperability ranking for mobile applications	Dragomir Yankov, Pavel Berkhin, Rajen Subba	In this paper we introduce the notion of interoperability ranking for mobile applications.
106	Sopra: a new social personalized ranking function for improving web search	Mohamed Reda Bouadjenek, Hakim Hacid, Mokrane Bouzeghoub	We present in this paper a contribution to IR modeling by proposing a new ranking function called SoPRa that considers the social dimension of the Web.
107	Browse with a social web directory	Hao Huang, Yunjun Gao, Lu Chen, Rui Li, Kevin Chiew, Qinming He	To improve users’ browse experiences and facilitate the web directory construction, in this paper, we propose a novel browse system called Social Web Directory (SWD for short) by integrating web directories and social bookmarks.
108	Who will retweet me?: finding retweeters in twitter	Zhunchen Luo, Miles Osborne, Jintao Tang, Ting Wang	Within a learning to-rank framework, we explore a wide range of features, such as retweet history, followers status, followers active time and followers interests.
109	A financial cost metric for result caching	Fethi Burak Sazoglu, B. Barla Cambazoglu, Rifat Ozcan, Ismail Sengor Altingovde, Özgür Ulusoy	In this paper, we propose a financial cost metric that goes one step beyond and takes also the hourly electricity prices into account when computing the cost.
110	Document classification by topic labeling	Swapnil Hingmire, Sandeep Chougule, Girish K. Palshikar, Sutanu Chakraborti	In this paper, we propose Latent Dirichlet Allocation (LDA) [1] based document classification algorithm which does not require any labeled dataset.
111	Mining web search topics with diverse spatiotemporal patterns	Di Jiang, Wilfred Ng	In this paper, we introduce the Spatiotemporal Search Topic Model (SSTM) to discover the latent topics from web search data with capturing their diverse spatiotemporal patterns simultaneously.
112	A novel topic model for automatic term extraction	Sujian Li, Jiwei Li, Tao Song, Wenjie Li, Baobao Chang	In this paper, we propose to compute termhood based on semantic representation of words.
113	Improving LDA topic models for microblogs via tweet pooling and automatic labeling	Rishabh Mehrotra, Scott Sanner, Wray Buntine, Lexing Xie	In this paper, we investigate methods to improve topics learned from Twitter content without modifying the basic machinery of LDA; we achieve this through various pooling schemes that aggregate tweets in a data preprocessing step for LDA.
114	Extractive summarisation via sentence removal: condensing relevant sentences into a short summary	Marco Bonzanini, Miguel Martinez-Alvarez, Thomas Roelleke	This research proposes an approach for extractive summarisation, supporting different scoring techniques, such as cosine similarity or divergence, as a method for finding representative sentences.
115	Characterizing stages of a multi-session complex search task through direct and indirect query modifications	Jiyin He, Marc Bron, Arjen P. de Vries	Instead of characterizing interaction behavior in terms of interface specific components, we propose to characterize users’ search behavior in terms of two types of query modification: (i) direct modification, which refers to reformulations of queries; and (ii) indirect modification, which refers to user operations on additional input components provided by various search interfaces.
116	Displaying relevance scores for search results	Guy Shani, Noam Tractinsky	In this paper we evaluate in a user study how users react to the display of such scores.
117	Studying page life patterns in dynamical web	Alexey Tikhonov, Ivan Bogatyy, Pavel Burangulov, Liudmila Ostroumova, Vitaliy Koshelev, Gleb Gusev	This paper focuses on the dynamical part of the web, i.e. pages that have a limited lifespan and experience a short popularity outburst within it.
118	A document rating system for preference judgements	Maryam Bashir, Jesse Anderton, Jie Wu, Peter B. Golbus, Virgil Pavlu, Javed A. Aslam	In this work, we consider the problem of inferring document relevance scores from pairwise preference judgments by analogy to tournaments using the Elo rating system.
119	Relevance dimensions in preference-based IR evaluation	Jinyoung Kim, Gabriella Kazai, Imed Zitouni	In this paper, we investigate how assessors determine their preference for one list of results over another with the aim to understand the role of various relevance dimensions in preference-based evaluation.
120	Composition of TF normalizations: new insights on scoring functions for ad hoc IR	François Rousseau, Michalis Vazirgiannis	In this paper, we propose a further level of abstraction, claiming that the successive normalizations are carried out through composition.
121	The impact of intent selection on diversified search evaluation	Tetsuya Sakai, Zhicheng Dou, Charles L.A. Clarke	In this study, we address the following research question: Does the choice of intents for a test collection affect relative performances of diversified search systems?
122	A comparison of the optimality of statistical significance tests for information retrieval evaluation	Julián Urbano, Mónica Marrero, Diego Martín	We present a large-scale study comprising nearly 60 million system comparisons showing that in practice the bootstrap, t-test and Wilcoxon test outperform the permutation test under different optimality criteria.
123	Assessor disagreement and text classifier accuracy	William Webber, Jeremy Pickens	In this paper, we examine the impact that disagreement between actual and authoritative assessor has upon classifier effectiveness, when evaluated against the authoritative conception.
124	Sequential testing in classifier evaluation yields biased estimates of effectiveness	William Webber, Mossaab Bagdouri, David D. Lewis, Douglas W. Oard	We demonstrate in this paper that such repeated testing leads to biased estimates of classifier effectiveness.
125	Relating retrievability, performance and length	Colin Wilkie, Leif Azzopardi	In this paper, we undertake an empirical investigation into the relationship between the retrievability of documents, the retrieval bias imposed by a retrieval system, and the retrieval performance, across different amounts of document length normalization.
126	Cumulative citation recommendation: classification vs. ranking	Krisztian Balog, Heri Ramampiaro	In this paper we perform an experimental comparison of these two strategies using supervised learning with a rich feature set.
127	Tagcloud-based explanation with feedback for recommender systems	Wei Chen, Wynne Hsu, Mong Li Lee	In this paper, we aim to increase the user acceptance of recommendations by providing more intuitive tag-based explanations of why the items are recommended.
128	Collaborative factorization for recommender systems	Chaosheng Fan, Yanyan Lan, Jiafeng Guo, Zuoquan Lin, Xueqi Cheng	To overcome the above problems, we propose a new framework for recommender systems, called collaborative factorization.
129	RecSys for distributed events: investigating the influence of recommendations on visitor plans	Richard Schaller, Morgan Harvey, David Elsweiler	In this work we investigate how visitors can be assisted by means of a recommender system via 2 large-scale naturalistic studies (n=860 and n=1047).
130	Ranking-oriented nearest-neighbor based method for automatic image annotation	Chaoran Cui, Jun Ma, Tao Lian, Xiaofang Wang, Zhaochun Ren	In this paper, we propose a ranking-oriented neighbor search mechanism to rank labeled images directly without going through the intermediate step of distance prediction.
131	Linking transcribed conversational speech	Joseph Malionek, Douglas W. Oard, Abhijeet Sangwan, John H.L. Hansen	This paper proposes automatically linking conversational speech to related resources as one way of supporting that sense-making task.
132	On contextual photo tag recommendation	Philip J. McParlane, Yashar Moshfeghi, Joemon M. Jose	In this paper, we propose a weighted tag recommendation model, building on an existing state-of-the-art, which varies the importance of time and location in the recommendation process, based on a given set of input tags.
133	The knowing camera: recognizing places-of-interest in smartphone photos	Pai Peng, Lidan Shou, Ke Chen, Gang Chen, Sai Wu	This paper presents a framework called Knowing Camera for real-time recognizing places-of-interest in smartphone photos, with the availability of online geotagged images of such places.
134	Question retrieval with user intent	Long Chen, Dell Zhang, Mark Levene	To address this problem, we present a hybrid approach that blends several language modelling techniques for question retrieval, namely, the classic (query-likelihood) language model, the state-of-the-art translation-based language model, and our proposed intent-based language model.
135	Mapping queries to questions: towards understanding users’ information needs	Yunjun Gao, Lu Chen, Rui Li, Gang Chen	In this paper, for the first time, we study the problem of mapping keyword queries to questions on community-based question answering (CQA) sites.
136	From keywords to keyqueries: content descriptors for the web	Tim Gollub, Matthias Hagen, Maximilian Michel, Benno Stein	To determine the keyqueries for a document, we present an exhaustive search algorithm along with effective pruning strategies.
137	Commodity query by snapping	Hao Huang, Yunjun Gao, Kevin Chiew, Qinming He, Lu Chen	In this paper, we propose a framework to address this issue by leveraging on various techniques, and evaluate the effectiveness and efficiency of this framework with experiments on a prototype.
138	Temporal variance of intents in multi-faceted event-driven information needs	Stewart Whiting, Ke Zhou, Joemon Jose, Mounia Lalmas	In this work we study the temporal variance of search intents for event-driven information needs using Wikipedia.
139	Pursuing insights about healthcare utilization via geocoded search queries	Shuang-Hong Yang, Ryen W. White, Eric Horvitz	We analyzed geotagged mobile queries in a privacy-sensitive study of potential transitions from health information search to in-world healthcare utilization.
140	Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures	Nima Asadi, Jimmy Lin	Given a fixed set of features and a learning-to-rank model, we explore effectiveness/efficiency tradeoffs with three candidate generation approaches: postings intersection with SvS, conjunctive query evaluation with WAND, and disjunctive query evaluation with WAND.
141	Estimating topical context by diverging from external resources	Romain Deveaud, Eric SanJuan, Patrice Bellot	We experiment in this paper a method that discounts documents based on their weighted divergence from a set of external resources.
142	Finding knowledgeable groups in enterprise corpora	Shangsong Liang, Maarten de Rijke	We introduce a group finding task: given a query topic, find knowledgeable groups that have expertise on that topic.
143	Neighbourhood preserving quantisation for LSH	Sean Moran, Victor Lavrenko, Miles Osborne	We introduce a scheme for optimally allocating multiple bits per hyperplane for Locality Sensitive Hashing (LSH).
144	Shame to be sham: addressing content-based grey hat search engine optimization	Fiana Raiber, Kevyn Collins-Thompson, Oren Kurland	We present an initial study identifying a form of content-based grey hat search engine optimization, in which a Web page contains both potentially relevant content and manipulated content: we call such pages sham documents, because they lie in the grey area between ‘ham’ (clearly normal) and ‘spam’ (clearly fake).
145	IRWR: incremental random walk with restart	Weiren Yu, Xuemin Lin	The main contribution of this paper is to devise an \emph{exact} and fast incremental algorithm of RWR for edge updates.
146	Bias-variance decomposition of ir evaluation	Peng Zhang, Dawei Song, Jun Wang, Yuexian Hou	In this paper, we present a unified formulation based on the bias-variance decomposition.
147	An adaptive evidence weighting method for medical record search	Dongqing Zhu, Ben Carterette	In this paper, we present a medical record search system which is useful for identifying cohorts required in clinical studies.
148	Fresh BrowseRank	Maxim Zhukovskiy, Andrei Khropov, Gleb Gusev, Pavel Serdyukov	This paper proposes a new method for computing page importance, referred to as Fresh BrowseRank.
149	Competition-based networks for expert finding	Çiğdem Aslay, Neil O’Hare, Luca Maria Aiello, Alejandro Jaimes	Addressing the problem of ranking users with respect to their expertise, we propose Competition-Based Expertise Networks (CBEN), a novel community expertise network structure based on the principle of competition among the answerers of a question.
150	A study on the accuracy of Flickr’s geotag data	Claudia Hauff	Here, we consider this assumption and investigate how accurate the provided location data is.
151	Finding impressive social content creators: searching for SNS illustrators using feedback on motifs and impressions	Yohei Seki, Kiyoto Miyajima	We propose a method for finding impressive creators in online social network sites (SNSs).
152	Informational friend recommendation in social media	Shengxian Wan, Yanyan Lan, Jiafeng Guo, Chaosheng Fan, Xueqi Cheng	In this paper, we propose to recommend friends according to the informational utility, which stands for the degree to which a friend satisfies the target user’s unfulfilled informational need, called informational friend recommendation.
153	Using social annotations to enhance document representation for personalized search	Mohamed Reda BOUADJENEK, Hakim Hacid, Mokrane Bouzeghoub, Athena Vakali	In this paper, we present a contribution to IR modeling.
154	The bag-of-repeats representation of documents	Matthias Gallé	We present new representations that avoid both pitfalls.
155	An LDA-smoothed relevance model for document expansion: a case study for spoken document retrieval	Debasis Ganguly, Johannes Leveling, Gareth J.F. Jones	This paper proposes a new DE technique providing a more uniform selection and weighting of DE terms from all constituent topics.
156	Timeline generation with social attention	Xin Wayne Zhao, Yanwei Guo, Rui Yan, Yulan He, Xiaoming Li	In this paper, we study how to incorporate social attention in the generation of timeline summaries. We construct four evaluation sets over six diverse topics.
157	Explicit feedback in local search tasks	Dmitry Lagun, Avneesh Sud, Ryen W. White, Peter Bailey, Georg Buscher	In this paper we describe a user study that examines the effect of offering searchers more control over how local preferences are gathered and used.
158	Ranking explanatory sentences for opinion summarization	Hyun Duk Kim, Malu G. Castellanos, Meichun Hsu, ChengXiang Zhai, Umeshwar Dayal, Riddhiman Ghosh	We propose and study several general methods for scoring the explanatoriness of a sentence. We introduce a novel sentence ranking problem called explanatory sentence extraction (ESE) which aims to rank sentences in opinionated text based on their usefulness for helping users understand the detailed reasons of sentiments (i.e., "explanatoriness").
159	#trapped!: social media search system requirements for emergency management professionals	Stefan Raue, Leif Azzopardi, Chris W. Johnson	In this short paper, we survey emergency management professionals to ascertain how social media is used when responding to incidents, the search strategies that they undertake, and the challenges that they face when using social media streams.
160	ThemeStreams: visualizing the stream of themes discussed in politics	Ork de Rooij, Daan Odijk, Maarten de Rijke	We describe ThemeStreams: a demonstrator that maps political discussions to themes and influencers and illustrate how this mapping is used in an interactive visualization that shows us which themes are being discussed, and that helps us answer the question "Who put this issue on the map?"
161	BATC: a benchmark for aggregation techniques in crowdsourcing	Quoc Viet Hung Nguyen, Thanh Tam Nguyen, Ngoc Tran Lam, Karl Aberer	In this paper, we develop a benchmarking tool that allows to (i) simulate the crowd and (ii) evaluate aggregate techniques in different aspects (accuracy, sensitivity to spammers, etc.).
162	Spacious: an interactive mental search interface	Phong D. Vo, Hichem Sahbi	We introduce in this work a novel approach for semantic indexing and mental image search.
163	Flex-BaseX: an XML engine with a flexible extension of Xquery full-text	Emanuele Panzeri, Gabriella Pasi	Flex-BaseX: an XML engine with a flexible extension of Xquery full-text
164	ProductSeeker: entity-based product retrieval for e-commerce	Hongzhi Wang, Xiaodong Zhang, Jianzhong Li, Hong Gao	This paper proposes ProductSeeker, a product retrieval system organizing results according to their referring real-world entities for the conveniences of users.
165	Live nuggets extractor: a semi-automated system for text extraction and test collection creation	Matthew Ekstrand-Abueg, Virgil Pavlu, Javed A. Aslam	Live nuggets extractor: a semi-automated system for text extraction and test collection creation
166	X-ENS: semantic enrichment of web search results at real-time	Pavlos Fafalios, Yannis Tzitzikas	In this paper, we present X-ENS (eXplore ENtities in Search), a web search application that enhances the classical, keyword-based, web searching with semantic information, as a means to combine the pros of both Semantic Web standards and common Web Searching.
167	Accurate and robust text detection: a step-in for text retrieval in natural scene images	Xu-Cheng Yin, Xuwang Yin, Kaizhu Huang, Hong-Wei Hao	We propose and implement a robust text detection system, which is a prominent step-in for text retrieval in natural scene images or videos.
168	A framework for specific term recommendation systems	Thomas Lüke, Philipp Schaer, Philipp Mayr	In this paper we present the IRSA framework that enables the automatic creation of search term suggestion or recommendation systems (TS).
169	TweetMogaz: a news portal of tweets	Walid Magdy	It creates a real-time comprehensive report about what people discuss and share around news happening in certain regions.
170	InfoLand: information lay-of-land for session search	Jiyun Luo, Dongyi Guan, Hui Yang	We present a new tool called InfoLand that integrates external knowledge from Wikipedia when building SRC hierarchies and increase their stability.
171	A portable multilingual medical directory by automatic categorization of Wikipedia articles	Fernando Ruiz-Rico, María-Consuelo Rubio-Sánchez, David Tomás, Jose-Luis Vicedo	In this paper we present an application that builds a hierarchical structure to organize all Wikipedia entries, so that medical articles can be reached from general to particular, using the well known Medical Subject Headings (MeSH) thesaurus.
172	A geolinguistic web application based on linked open data	Emanuele Di Buccio, Giorgio Maria Di Nunzio, Gianmaria Silvello	In this demo, we propose a Linked Open Data approach for increasing the level of interoperability of geolinguistic applications and the reuse of the data.
173	TopicVis: a GUI for topic-based feedback and navigation	Debasis Ganguly, Manisha Ganguly, Johannes Leveling, Gareth J.F. Jones	This paper describes a search system which includes topic model visualization to improve the user search experience.
174	Information seeking in digital cultural heritage with PATHS	Mark M. Hall, Paul D. Clough, Samuel Fernando, Paula Goodale, Mark Stevenson, Eneko Agirre, Arantxa Otegi, Aitor Soroa, Kate Fernie, Jillian Griffiths, Runar Bergheim	Information seeking in digital cultural heritage with PATHS
175	Answering natural language queries over linked data graphs: a distributional semantics approach	André Freitas, Fabrício F. de Faria, Seán O’Riain, Edward Curry	This paper demonstrates Treo, a natural language query mechanism for Linked Data graphs.
176	Removing the mismatch headache in XML keyword search	Yong Zeng, Zhifeng Bao, Tok Wang Ling, Guoliang Li	We propose a practical yet efficient way to detect the MisMatch problem and generate helpful suggestions to users, namely MisMatch detector and suggester.
177	YaLi: a crowdsourcing plug-in for NERD	Yafang Wang, Lili Jiang, Johannes Hoffart, Gerhard Weikum	From the research perspective, we aim to improve the methods that are used for named entity recognition and disambiguation (NERD) by leveraging the plug-in as an implicit crowdsourcing platform.
178	SearchResultFinder: federated search made easy	Dolf Trieschnigg, Kien Tjin-Kam-Jet, Djoerd Hiemstra	In this demonstration we present SearchResultFinder, a browser plugin which speeds up determining reusable XPaths for extracting search result items from HTML search result pages.
179	Online matching of web content to closed captions in IntoNow	Carlos Castillo, Gianmarco De Francisci Morales, Ajay Shekhawat	The system we demonstrate is activated by IntoNow for specific types of shows.
180	Match the news: a firefox extension for real-time news recommendation	Margarita Karkali, Dimitris Pontikis, Michalis Vazirgiannis	We present Match the News, a browser extension for real time news recommendation.
181	Demonstration of citation pattern analysis for plagiarism detection	Bela Gipp, Norman Meuschke, Corinna Breitinger, Mario Lipinski, Andreas Nürnberger	Demonstration of citation pattern analysis for plagiarism detection
182	A multilingual and multiplatform application for medicinal plants prescription from medical symptoms	Fernando Ruiz-Rico, David Tomás, Jose-Luis Vicedo, María-Consuelo Rubio-Sánchez	This paper presents an application for medicinal plants prescription based on text classification techniques.
183	Searching in the city of knowledge: challenges and recent developments	Veli Bicer, Vanessa Lopez	This tutorial will present deep insights, challenges, opportunities and techniques to make heterogeneous city data searchable and show how emerging IR techniques models can be employed to retrieve relevant information for the citizens.
184	Scalability and efficiency challenges in commercial web search engines	B. Barla Cambazoglu, Ricardo Baeza-Yates	The main objective of this tutorial is to provide an overview of the fundamental scalability and efficiency challenges in commercial web search engines, bridging the existing gap between the industry and academia.
185	Music similarity and retrieval	Peter Knees, Markus Schedl	Apart from explaining approaches that estimate similarity based on acoustic properties of an audio signal, we review methods that exploit (mostly textual) meta-data from the Web to build representations of music then used for similarity calculation.
186	The cluster hypothesis in information retrieval	Oren Kurland	The cluster hypothesis in information retrieval
187	Entity linking and retrieval	Edgar Meij, Krisztian Balog, Daan Odijk	This full-day tutorial presents a comprehensive introduction to entity linking and retrieval.
188	Kernel-based learning to rank with syntactic and semantic structures	Alessandro Moschitti	This tutorial aims at introducing essential and simplified theory of Support Vector Machines and KMs for the design of practical applications.
189	Designing search usability	Tony Russell-Rose	The aim of this tutorial is to deliver a course grounded in good scholarship, integrating the latest research findings with insights derived from the practical experience of designing and optimizing an extensive range of commercial search applications.
190	Diversity and novelty in information retrieval	Rodrygo L.T. Santos, Pablo Castells, Ismail Sengor Altingovde, Fazli Can	Diversity and novelty in information retrieval
191	Multimedia recommendation: technology and techniques	Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui	When looking back, the information retrieval (IR) community has a long history of studying and contributing recommender system design and related issues.
192	Building test collections: an interactive tutorial for students and others without their own evaluation conference series	Ian M. Soboroff	The goal of this tutorial is to lay out issues, procedures, pitfalls, and practical advice.
193	Workshop on benchmarking adaptive retrieval and recommender systems: BARS 2013	Pablo Castells, Frank Hopfgartner, Alan Said, Mounia Lalmas	Workshop on benchmarking adaptive retrieval and recommender systems: BARS 2013
194	SIGIR 2013 workshop on modeling user behavior for information retrieval evaluation	Charles L.A. Clarke, Luanne Freund, Mark D. Smucker, Emine Yilmaz	The SIGIR 2013 Workshop on Modeling User Behavior for Information Retrieval Evaluation (MUBE 2013) brings together people to discuss existing and new approaches, ways to collaborate, and other ideas and issues involved in improving information retrieval evaluation through the modeling of user behavior.
195	Internet advertising: theory and practice	Bin Gao, Jun Yan, Dou Shen, Tie-Yan Liu	The main purpose of this workshop is to bring together researchers and practitioners in the area of Internet Advertising and enable them to share their latest research results, to express their opinions, and to discuss future directions.
196	Exploration, navigation and retrieval of information in cultural heritage: ENRICH 2013	Séamus Lawless, Maristella Agosti, Paul Clough, Owen Conlan	Exploration, navigation and retrieval of information in cultural heritage: ENRICH 2013
197	SIGIR 2013 workshop on time aware information access (#TAIA2013)	Fernando Diaz, Susan Dumais, Miles Efron, Kira Radinsky, Maarten de Rijke, Milad Shokouhi	We aim to bring together practitioners and researchers to discuss their recent breakthroughs and the challenges with addressing time-aware information access, both from the algorithmic and the architectural perspectives.
198	Workshop on health search and discovery: helping users and advancing medicine	Ryen W. White, Elad Yom-Tov, Eric Horvitz, Eugene Agichtein, William Hersh	Workshop on health search and discovery: helping users and advancing medicine
199	EuroHCIR2013: the 3rd European workshop on human-computer interaction and information retrieval	Max L. Wilson, Birger Larsen, Preben Hansen, Kristian Norling, Tony Russell-Rose	EuroHCIR2013: the 3rd European workshop on human-computer interaction and information retrieval
200	Beyond relevance: on novelty and diversity in tag recommendation	Fabiano Belém	We propose to explicitly exploit issues related to novelty and diversity in tag recommendation tasks, an unexplored research avenue (only relevance issues have been investigated so far), in order to improve user experience and satisfaction.
201	Group-support for task-based information searching: a knowledge-based approach	Thilo Boehm	Group-support for task-based information searching: a knowledge-based approach
202	Diversified relevance feedback	Matt Crane	The primary technique being researched now is diversification, which aims to populate the results with a set of documents that cover different possible interpretations for the query, while maintaining a degree of relevance, as determined by the search engine.
203	Segmentation strategies for passage retrieval in audio-visual documents	Petra Galuščáková	In this work, we examine two general strategies for Passage Retrieval: blind segmentation into overlapping regular-length passages and segmentation into variable-length passages based on semantics of their content.
204	Indexing and querying overlapping structures	Faegheh Hasibi	This research attempts to index overlapping structures and provide efficient query processing for large-scale search engines.
205	A query and patient understanding framework for medical records search	Nut Limsopatham	Indeed, we propose to build a query and patient understanding framework that can gain insights from EMRs and queries, by modelling and reasoning during retrieval in terms of the four aforementioned aspects (symptom, diagnostic test, diagnosis, and treatment) at three different levels of the retrieval process.
206	Semantic models for answer re-ranking in question answering	Piero Molino	The importance and effectiveness of linguistically motivated features, obtained from syntax, lexical semantics and semantic role labeling, was shown in literature [2-4], but there are still several different possible semantic features that have not been taken into account so far and our goal is to find out if their use could lead to performance improvement.
207	Task differentiation for personal search evaluation	Seyedeh Sargol Sadeghi	Task differentiation for personal search evaluation
208	The role of current working context in professional search	Maya Sappelli	In the PhD project presented in this abstract we aim at maintaining well-being at work through information support.
209	How far will you go?: characterizing and predicting online search stopping behavior using information scent and need for cognition	Wan-Ching Wu	How far will you go?: characterizing and predicting online search stopping behavior using information scent and need for cognition
210	Effective approaches to retrieving and using expertise in social media	Reyyan Yeniterzi	In this work, we propose to develop expert retrieval approaches which will handle these challenges while making use of the advantages.