SIGIR 2014 Full Papers
Included here is a tentative list of the full papers and their allocation into sessions. Note: titles, author lists, and allocations are subject to change.
Tuesday-1a
Risks and Rewards (Room 5, 10:30-11:45)
•Modelling Interaction with Economic Models of SearchLeif Azzopardi (University of Glasgow)
•Query-Performance Prediction: Setting the Expectations StraightFiana Raiber (Technion - Israel Institute of Technology), Oren Kurland (Technion)
•Hypothesis Testing for Risk-Sensitive Evaluation of Retrieval SystemsBekir Taner Dincer (Mugla University), Craig Macdonald (U. Glasgow), Iadh Ounis (University of Glasgow)
Tuesday-1b
#microblog #sigir2014 (Room 6, 10:30-11:45)
•Temporal Feedback for Tweet Search with Non-Parametric Density EstimationMiles Efron (University of Illinois), Jimmy Lin (University of Maryland), Jiyin He (Centrum Wiskunde Informatica), Arjen P. de Vries (Centrum Wiskunde & Informatica)
•Fine-Grained Location Extraction from Tweets with Temporal AwarenessChenliang Li (Wuhan University), Aixin Sun (Nanyang Technological University)
•Collaborative Personalized Twitter Search with Topic-Language ModelsJan Vosecky (HKUST), Kenneth Wai-Ting Leung (HKUST), Wilfred Ng (HKUST)
Tuesday-1c
Recommendation (Room 7, 10:30-11:45)
•Gaussian Process Factorization Machines for Context-aware RecommendationsTrung Nguyen (NICTA & ANU), Alexandros Karatzoglou (Telefonica Research), Linas Baltrunas (Telefonica Research)
•Addressing Cold Start in Recommender Systems: A Semi-supervised Co-training AlgorithmMi Zhang (Fudan University), Jie Tang (Tsinghua University), Xuchen Zhang (Fudan University), Xiangyang Xue
•Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment AnalysisYongfeng Zhang (Tsinghua University), Min Zhang (Dept of Computer Science, Tsinghua University), Yi Zhang (Unversity of California Santa Cruz)
Tuesday-2a
(I Can't Get No) Satisfaction (Room 5, 1:15-2:55)
•Context-Aware Web Search Abandonment PredictionYang Song (Microsoft Research, Redmond), Xiaolin Shi (Microsoft), Ryen W. White (Microsoft Research), Ahmed Hassan (Microsoft Research)
•Impact of Response Latency on User Behavior in Web SearchIoannis Arapakis (Yahoo Labs Barcelona), Xiao Bai (Yahoo Labs, Barcelona), B. Barla Cambazoglu (Yahoo Labs)
•Towards Better Measurement of Attention and Satisfaction in Mobile SearchDmitry Lagun (Emory University), Chih-Hung Hsieh (Google), Dale Webster (Google), Vidhya Navalpakkam (Google)
•Modeling Action-level Satisfaction for Search Task Satisfaction PredictionHongning Wang (University of Illinois at Urbana-Champaign), Yang Song (Microsoft Research, Redmond), Ming-Wei Chang (Microsoft Research), Xiaodong He (Microsoft Research), Ahmed Hassan (Microsoft Research), Ryen W. White (Microsoft Research)
Tuesday-2b
Doctors and Lawyers (Room 6, 1:15-2:55)
•Circumlocution in Diagnostic Medical QueriesIsabelle Stanton (UC Berkeley), Samuel Ieong (Microsoft Research), Nina Mishra (Microsoft Research)
•Interactions between Health Searchers and Search EnginesGeorg Schoenherr (Carnegie Mellon University), Ryen W. White (Microsoft Research)
•Evaluation of Machine Learning Protocols for Technology-Assisted Review in Electronic DiscoveryGordon V. Cormack (University of Waterloo), Maura R. Grossman (Wachtell, Lipton, Rosen & Katz)
•ReQ-ReC: High-Recall Retrieval with Rate-Limited QueriesCheng Li (University of Michigan), Yue Wang (University of Michigan), Paul Resnick (University of Michigan), Qiaozhu Mei (University of Michigan)
Tuesday-2c
Hashing and Efficiency (Room 7, 1:15-2:55)
•Supervised Hashing with Latent Factor ModelsPeichao Zhang (Shanghai Jiao Tong University), Wei Zhang (Shanghai Jiao Tong University), Wu-Jun Li (Nanjing University), Minyi Guo (Shanghai Jiao Tong University)
•Preference Preserving Hashing for Efficient RecommendationZhiwei Zhang (Purdue University), Qifan Wang (Purdue University), Lingyun Ruan (Purdue University), Luo Si (Purdue University)
•Load Balancing for Partition-based Similarity SearchXun Tang (University of California at Santa Barbara), Maha Alabduljalil (UCSB), Xin Jin, Tao Yang (University of California at Santa Barbara)
•Estimating Global Statistics for Unstructured P2P Search in the Presence of Adversarial PeersSami Richardson (University College London), Ingemar Cox (University College London)
Tuesday-3a
Social Media (Room 5, 3:25-5:05)
•Hierarchical Multi-Label Classification of Social Text StreamsZhaochun Ren (University of Amsterdam), Maria-Hendrike Peetz (University of Amsterdam), Shangsong Liang (U. of Amsterdam), Willemijn van Dolen, Maarten de Rijke (University of Amsterdam)
•An Adaptive Teleportation Random Walk Model for Learning Social Tag RelevanceXiaofei Zhu (L3S Research Center), Wolfgang Nejdl (L3S Research Center), Mihai Georgescu (L3S Research Center)
•Predicting the Popularity of Web 2.0 Items Based on User CommentsHe Xiangnan (National University of Singapore), Ming Gao (Singapore Management University), Min-Yen Kan (National University of Singapore), Yiqun Liu (Tsinghua University), Kazunari Sugiyama (School of Computing)
•Recommending Social Media Content to Community Owners Inbal Ronen (IBM), Ido Guy (IBM Research India), Elad Kravi (Technion - Israel Institute of Technology), Maya Barnea (IBM Research)
Tuesday-3b
Indexing and Efficiency (Room 6, 3:25-5:05)
•Predictive Parallelization: Taming Tail Latencies in Web SearchMyeongjae Jeon (Rice University), Saehoon Kim (POSTECH), Seung-Won Hwang (POSTECH), Yuxiong He (Microsoft Research), Sameh Elnikety (Microsoft Research), Alan Cox (Rice University), Scott Rixner (Rice University)
•Skewed Partial Bitvectors for List IntersectionAndrew Kane (University of Waterloo), Frank Tompa (University of Waterloo)
•Partitioned Elias-Fano IndexesGiuseppe Ottaviano (ISTI-CNR), Rossano Venturini (University of Pisa)
•Principled Dictionary Pruning for Low-Memory Corpus CompressionJiancong Tong (Nankai University), Anthony Wirth (The University of Melbourne), Justin Zobel (University of Melbourne)
Tuesday-3c
E Pluribus Unum (Room 7, 3:25-5:05)
•Learning for Search Result DiversificationYadong Zhu (ICT)
•Fusion Helps DiversificationShangsong Liang (U. of Amsterdam), Zhaochun Ren (University of Amsterdam), Maarten de Rijke (University of Amsterdam)
•Utilizing Relevance Feedback in Fusion-Based RetrievalElla Rabinovich (IBM Research Lab, Haifa), Oren Kurland (Technion)
•A Simple Term Frequency Transformation Model for Effective Pseudo Relevance FeedbackZheng Ye (York University, Toronto, Ontario, Canada), Jimmy Huang (York University, Toronto, Ontario, Canada)
Wednesday-4a
Think Globally, Act Locally (Room 5, 10:30-11:45)
•Who is the Barbecue King of Texas?: A Geo-Spatial Approach to Finding Local ExpertsZhiyuan Cheng (Texas A&M University), James Caverlee (Texas A&M University), Himanshu Barthwal (Texas A&M University), Vandana Bachani (Texas A&M University)
•Your Neighbors Affect Your Ratings: On Geographical Neighborhood Influence to Rating PredictionLongke Hu (Nanyang Technological University), Aixin Sun (Nanyang Technological University), Yong Liu (Nanyang Technological University)
•Processing Spatial-keyword Query as a Top-k Aggregation Query Dongxiang Zhang (National University of Singapore), Chee-Yong Chan, Kian-Lee Tan
Wednesday-4b
Scientia Potentia Est (Room 6,10:30-11:45)
•Entity Query Feature Expansion using Knowledge Base LinksJeffrey Dalton (CIIR, University of Massachusetts Amhest), James Allan (University of Massachusetts Amherst), Laura Dietz (CIIR, University of Massachusetts Amhest)
•QUADS: Question Answering for Decision SupportZi Yang (Carnegie Mellon University), Eric nyberg
•Topic Labeled Text Classification: A Weakly Supervised ApproachSwapnil Hingmire (Tata Research Development And Design Centre), Sutanu Chakraborti (IIT Madras, India)
Wednesday-4c
More Hashing (Room 7, 10:30-11:45)
•Discriminative Coupled Dictionary Hashing for Fast Cross-media RetrievalZhou Yu (Zhejiang University), Fei Wu (Zhejiang University), Yi Yang (University of Queensland), Qi Tian (University of Texas at San Antonio now at Microsoft Research), Jiebo Luo (University of Rochester), Yueting Zhuang (Zhejiang University)
•Active Hashing with Joint Data Example and Tag SelectionQifan Wang (Purdue University), Luo Si (Purdue University)
•Latent Semantic Sparse Hashing for Cross-Modal Similarity SearchZhou Jile (Tsinghua University), Guiguang Ding (Tsinghua University), Yuchen Guo (Tsinghua University)
Wednesday-5a
Brains!!! (Room 5, 3:25-4:15)
•Predicting Term-Relevance from Brain SignalsManuel J. A. Eugster (Helsinki Institute for Information Technology), Ruotsalo Tuukka (Helsinki Institute for Information Technology), Michiel M SpapÈ (Helsinki Institute for Information Technology), Ilkka Kosunen (University of Helsinki), Oswald Barral (University of Helsinki), Niklas Ravaja (University of Helsinki), Giulio Jacucci (University of Helsinki), Samuel Kaski (Aalto University)
•Multidimensional Relevance Modeling via Psychometrics and CrowdsourcingYinglong Zhang (University of Texas at Austin), Jin Zhang (University of Texas at Austin ), Matthew Lease (University of Texas at Austin), Jacek Gwizdka (University of Texas at Austin )
Wednesday-5b0
Auto-completio (Room 6, 3:25-4:15)
•Learning User Reformulation Behavior for Query Auto-completionJyun-Yu Jiang (National Taiwan University), Pu-Jen Cheng (Dept. of CSIE, National Taiwan University)
•A Two-dimensional Click Model for Query Auto-completionYanen Li (University of Illinois at Urbana-Champaign), Anlei Dong (Yahoo! Labs), Hongning Wang (University of Illinois at Urbana-Champaign), Hongbo Deng (Yahoo Labs), Yi Chang (Yahoo Labs), ChengXiang Zhai (University of Illinois at Urbana-Champaign)
Wednesday-5b1
How to Win Friends and Influence People (Room 6, 4:15-5:05)
•On Measuring Social Friend Interest Similarities in Recommender SystemsHao Ma (Microsoft Research)
•IMRank: Influence Maximization via Finding Self-Consistent RankingSuqi Cheng (Institute of Computing Technology), Huawei Shen (Institute of Computing Technology, CAS), Junming Huang (Institute of Computing Technology, CAS), Wei Chen (Institute of Computing Technology, CAS), Xueqi Cheng (Institute of Computing Technology, CAS)
Wednesday-5c
Collaborative Complex Personalization(Room 7, 3:25-5:05)
•User-Driven System-Mediated Collaborative Information RetrievalLaure Soulier (IRIT - University Paul sabatier), Chirag Shah (Rutgers University), Lynda Tamine (IRIT - University of Toulouse)
•SearchPanel: Framing Complex Search NeedsPernilla Qvarfordt (FX Palo Alto Laboratory, Inc.), Simon Tretter (University of Amsterdam), Gene Golovchinsky (FX Palo Alto Laboratory), Tony Dunnigan (FX Palo Alto Laboratory, Inc.)
•Cohort Modeling for Enhanced Personalized SearchJinyun Yan (Rutgers University), Wei Chu (Microsoft Bing), Ryen W. White (Microsoft Research)
•Characterizing Multi-Click Behavior and the Risks and Opportunities of Changing Results during UseChia-Jung Lee (University of Massachusetts Amherst), Jaime Teevan (Microsoft Research), Sebastian de la Chica (Microsoft Bing)
Thursday-6a
#moremicroblog #sigir2014 (Room 5, 10:30-11:45)
•Learning Similarity Functions for Topic Detection in Online Reputation MonitoringDamiano Spina (UNED NLP & IR Group), Julio Gonzalo (UNED), Enrique Amigó (UNED)
•Predicting Trending Messages and Diffusion Participants in Microblogging NetworkJingwen Bian (National University of Singapore), Yang Yang (National University of Singapore), Tat Seng Chua (National University of Singapore)
•Leveraging Knowledge across Media for Spammer Detection in MicrobloggingXia Hu (Arizona State University), Jiliang Tang (Arizona State University), Huan Liu
Thursday-6b
Scents and Sensibility (Room 6, 10:30-11:45)
•Using Information Scent and Need for Cognition to Understand Online Search Behavior Wan-Ching Wu (University of North Carolina at Chapel Hill), Diane Kelly (University of North Carolina Chapel Hill), Avneesh Sud (Microsoft Bing)
•Discrimination Between Tasks with User Activity Patterns During Information SearchMichael J. Cole (Rutgers University), Chathra Hendahewa (Rutgers Univesity), Nicholas J Belkin (Rutgers, The State University of New Jersey), Chirag Shah (Rutgers University)
•Investigating Users' Query Formulations for Cognitive Search IntentsMakoto Kato (Kyoto University), Takehiro Yamamoto (Kyoto University), Hiroaki Ohshima (Kyoto University), Katsumi Tanaka (Kyoto University)
Thursday-6c
Users vs. Models (Room 7, 10:30-11:45)
•Win-Win Search: Dual-Agent Stochastic Game in Session SearchJiyun Luo (Georgetown University), Sicong Zhang (Georgetown University), Grace Hui Yang (Georgetown University)
•Injecting User Models and Time into Precision via Markov ChainsMarco Ferrante (University of Padua), Nicola Ferro (University of Padua), Maria Maistro (University of Padua)
•Searching, Browsing, and Clicking in a Search SessionJiepu Jiang (University of Massachusetts Amherst), Daqing He (University of Pittsburgh), James Allan (University of Massachusetts Amherst)
Thursday-7a
Sentiments (Room 5, 1:40-2:55)
•Coarse-to-Fine Review Selection via Supervised Joint Aspect and Sentiment ModelZhen Hai (Nanyang Technological University, Singapore), Gao Cong, Kuiyu Chang (Nanyang Technological University, Singapore), Wenting Liu (Nanyang Technological University, Singapore), Peng Cheng (Nanyang Technological University, Singapore)
•Cross-Domain and Cross-Category Emotion Tagging for Comments of Online NewsNing Zhang (Purdue University), Ying Zhang (Nankai University), Luo Si (Purdue University), Yanshan Lu (Purdue University), Xiaojie Yuan (NanKai University)
•Economically-Efficient Sentiment Stream AnalysisRoberto Lourenco de Oliveira Junior (UFMG), Adriano Veloso (UFMG), Wagner Meira Jr. (UFMG), Adriano Pereira (UFMG), Renato Ferreira (UFMG), Srinivasan Parthasarathy (OSU)
Thursday-7b
More Like Those (Room 6, 1:40-2:55)
•New and Improved: Modeling Versions to Improve App RecommendationJovian Lin (National University of Singapore), Kazunari Sugiyama (School of Computing), Min-Yen Kan (National University of Singapore), Tat Seng Chua (National University of Singapore)
•Bundle Recommendation in eCommerceZhu Tao (WalmartLabs), Patrick Harrington (WalmartLabs), Junjun Li (WalmartLabs), Lei Tang (WalmartLabs)
•Does Product Recommendation Meet its Waterloo in Unexplored Categories? No, Price Comes to HelpChen Jia (Shanghai Jiaotong University), Qin Jin (Renmin University of China), Shiwan Zhao (IBM CRL), Shenghua Bao (IBM CRL), Li Zhang (IBM CRL), Zhong Su (IBM CRL), Yong Yu (Shanghai Jiaotong University)
Thursday-7c
Signs and Symbols (Room 7, 1:40-2:55)
•Query Expansion for Cross-script Information RetrievalParth Gupta (UPV), Monojit Choudhury (Microsoft Research India), Rafael Banchs (Institute for Infocomm Research), Paolo Rosso, Kalika Bali (Microsoft Research India)
•Retrieval of Similar Chess PositionsDebasis Ganguly (Dublin City University)
•A Mathematics Retrieval System for Formulae in Layout PresentationsXiaoyan Lin (Peking University), Liangcai Gao, Xuan Hu, Xiaozhong Liu (Indiana University Bloomington), Zhi Tang
Thursday-8a
Picture This (Room 5, 3:25-5:05)
•Recognizing and Annotating Places-of-Interest in Smartphone PhotosPai Peng, Lidan Shou, Chen Ke, Chen Gang, Sai Wu
•Click-through-based Cross-view Learning for Image SearchYingwei Pan (University of Science and Technology of China), Ting Yao (City University of Hong Kong), Tao Mei (Microsoft Research), Houqiang Li (University of Science and Technology of China), Chong-Wah Ngo, Yong Rui (Microsoft Research)
•Learning to Personalize Trending Image Search SuggestionChun-Che Wu (National Taiwan University), Tao Mei (Microsoft Research), Winston H. Hsu (Dept. of Computer Science and Information Eng), Yong Rui (Microsoft Research)
•PRISM: Concept-preserving Social Image Search Results SummarizationBoon-Siew Seah (Nanyang Technological University), Sourav S. Bhowmick (Nanyang Technological University), Aixin Sun (Nanyang Technological University)
Thursday-8b
Time and Tide (Room 6, 3:25-5:05)
•Time-Critical SearchNina Mishra (Microsoft Research), Ryen W. White (Microsoft Research), Samuel Ieong (Microsoft Research), Eric Horvitz (Microsoft Research)
•Learning Temporal-Dependent Ranking ModelsMiguel Costa (Large-Scale Informatics Systems Laboratory ), M·rio Silva, Francisco Couto
•Web Page Segmentation with Structured Prediction and its Application in Web Page ClassificationLidong Bing (The Chinese University of Hong Kong), Rui Guo (Baidu Inc.), Wai Lam (The Chinese University of Hong Kong), Zhengyu Niu (Baidu Inc.), Wang Haifeng
•Query Log Driven Web Search Results ClusteringJose Moreno (University of Caen), GaÎl Dias (Normandie University), Guillaume Cleuziou (University of Orléans)
Thursday-8c0
Summaries and Semantics (Room 7, 3:25-4:15)
•CTSUM: Extracting More Certain Summaries for News ArticlesXiaojun Wan (Peking University), Jianmin Zhang (Peking University & Beijing Normal University)
•Continuous Word Embeddings for Detecting Local Text Reuses at the Semantic LevelQi Zhang (Fudan University), Jihua Kang (Fudan University), Jin Qian (Fudan University), Xuanjing Huang (Fudan University)
Thursday-8c1
[Citation] Recommendation (Room 7, 4:15-5:05)
•CiteSight: Supporting Contextual Citation Recommendation Using Differential SearchAvishay Livne (University of Michigan), Vivek Gokuladas (University of Michigan), Jaime Teevan (Microsoft Research), Susan T Dumais (Microsoft Research Redmond), Eytan Adar (University of Michigan)
•Cross-language Context-Aware Citation Recommendation in Scientific ArticlesXuewei Tang (Peking University), Xiaojun Wan (Peking University), Xun Zhang (Peking University)