Program at a Glance 

Session 1A: New IR Applications
July 9 (Monday), 10:30 – 12:00, Hussey (Floor 2)
Chair: Debora Donato (Mix Tech)

• Neural Compatibility Modeling with Attentive Knowledge Distillation
  Xuemeng Song (Shandong University); Fuli Feng (National University of Singapore); Xianjing Han (Shandong University); Xin Yang (Shandong University); Wei Liu (Tencent AI Lab); Liqiang Nie (Shandong University)
• Attentive Moment Retrieval in Videos
  Meng Liu (Shandong University); Xiang Wang (National University of Singapore); Liqiang Nie (Shandong University); Xiangnan He (National University of Singapore); Baoquan Chen (Shandong University); Tat-Seng Chua (National University of Singapore)
• Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach
  Chuan Qin (University of Science and Technology of China); Hengshu Zhu (Talent Intelligence Center, Baidu, inc.); Tong Xu (University of Science and Technology of China); Chen Zhu (Talent Intelligence Center, Baidu, inc.); Liang Jiang (University of Science and Technology of China); Enhong Chen (University of Science and Technology of China); Hui Xiong (Rutgers University)
• Cross-modal retrieval in the cooking context: Learning semantic text-image embeddings
  Micael Carvalho (Sorbonne Université); Remi Cadene (Sorbonne Université); David Picard (Sorbonne Université); Laure Soulier (Sorbonne Université); Nicolas Thome (Conservatoire national des arts et métiers); Matthieu Cord (Sorbonne Université)

Session 1B: Log Analysis
July 9 (Monday), 10:30 – 12:00, Vanderberg (Floor 2)
Chair: Paul Bennett (Microsoft Research)

• A Click Sequence Model for Web Search
  Alexey Borisov (Yandex & University of Amsterdam); Martijn Wardenaar (University of Amsterdam); Ilya Markov (University of Amsterdam); Maarten de Rijke (University of Amsterdam)
• Understanding and Evaluating User Satisfaction with Music Discovery
  Jean Garcia-Gathright (Spotify); Brian St. Thomas (Spotify); Christine Hosey (Spotify); Zahra Nazari (Spotify); Fernando Diaz (Microsoft)
• Identifying Users behind Shared Accounts in Online Streaming Services
  Jyun-Yu Jiang (University of California, Los Angeles); Cheng-Te Li (National Cheng Kung University); Yian Chen (KKBOX Inc.,); Wei Wang (University of California, Los Angeles)
• Predicting User Knowledge Gain in Informational Search Sessions
  Ran Yu (L3S Research Center); Ujwal Gadiraju (L3S Research Center); Peter Holtz (Leibniz-Institut für Wissensmedien (IWM)); Markus Rokicki (L3S Research Center); Philipp Kemkes (L3S Research Center); Stefan Dietze (L3S Research Center)

Session 1C: Predictions
July 9 (Monday), 10:30 – 12:00, Michigan (Floor 2)
Chair: Alistair Moffat (The University of Melbourne)

• Dynamic Shard Cutoff Prediction for Selective Search
  Hafeezul Rahman Mohammad (Carnegie Mellon University); Keyang Xu (Petuum Inc.); Jamie Callan (Carnegie Mellon University); J. Shane Culpepper (RMIT University)
• Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
  Guokun Lai (Carnegie Mellon University); Wei-Cheng Chang (Carnegie Mellon University); Yiming Yang (Carnegie Mellon University); Hanxiao Liu (Carnegie Mellon University)
• Neural Query Performance Prediction using Weak Supervision from Multiple Signals
  Hamed Zamani (University of Massachusetts Amherst); W. Bruce Croft (University of Massachusetts Amherst); J. Shane Culpepper (RMIT University)
• Combined Regression and Tripletwise Learning for Conversion Rate Prediction in Real-Time Bidding Advertising
  Lili Shan (Harbin Institute of Technology); Lei Lin (Harbin Institute of Technology); Chengjie Sun (Harbin Institute of Technology)

Session 1D: Learning to Rank I
July 9 (Monday), 10:30 – 12:00, Mendelssohn Theatre
Chair: Liangjie Hong (Etsy)

• From Greedy Selection to Exploratory Decision-Making: Diverse Ranking with Policy-Value Networks
  Yue Feng (Institute of Computing Technology, Chinese Academy of Sciences); Jun Xu (Institute of Computing Technology, Chinese Academy of Sciences); Yanyan Lan (Institute of Computing Technology, Chinese Academy of Sciences); Jiafeng Guo (Institute of Computing Technology, Chinese Academy of Sciences); Zeng Wei (Institute of Computing Technology, Chinese Academy of Sciences); Xueqi Cheng (Institute of Computing Technology, Chinese Academy of Sciences)
• Learning a Deep Listwise Context Model for Ranking Refinement
  Qingyao Ai (University of Massachusetts Amherst); Keping Bi (University of Massachusetts Amherst); Jiafeng Guo (Institute of Computing Technology, Chinese Academy of Sciences); W. Bruce Croft (University of Massachusetts Amherst)
• Efficient Exploration of Gradient Space for Online Learning to Rank
  Huazheng Wang (University of Virginia); Ramsey Langley (University of Virginia); Sonwoo Kim (University of Virginia); Eric McCord-Snook (University of Virginia); Hongning Wang (University of Virginia)
• Selective Gradient Boosting for Effective Learning to Rank
  Claudio Lucchese (ISTI-CNR); Franco Maria Nardini (ISTI-CNR); Raffaele Perego (ISTI-CNR); Salvatore Orlando (Università Ca’ Foscari Venezia); Salvatore Trani (ISTI CNR, Pisa)

Session 2A: Sentiment & Opinion
July 9 (Monday), 13:30 – 15:00, Hussey (Floor 2)
Chair: Min Zhang (Tsinghua University)

• Explainable Recommendation via Multi-Task Learning in Opinionated Text Data
  Nan Wang (Shanghai Jiao Tong University); Hongning Wang (University of Virginia); Yiling Jia (University of Virginia); Yue Yin (University of Virginia)
• Sentiment Analysis of Peer Review Texts for Scholarly Papers
  Ke Wang (Peking University); Xiaojun Wan (Peking University)
• Encoding syntactic knowledge in neural networks for sentiment classification (TOIS)
  Minlie Huang (Tsinghua University), Qiao Qian (Tsinghua University), Xiaoyan Zhu (Tsinghua University)
• A meta-framework for modeling the human reading process in sentiment analysis (TOIS)
  Ramy Baly (American University of Beirut), Roula Hobeica (American University of Beirut), Hazem Hajj (American University of Beirut), Wassim El-Hajj (American University of Beirut), Khaled Bashir Shaban (Qatar University), Ahmad Al-Sallab (Cairo University)

Session 2B: Social
July 9 (Monday), 13:30 – 15:00, Vanderberg (Floor 2)
Chair: Vanessa Murdock (Amazon Research)

• Attentive Recurrent Social Recommendation
  Peijie Sun (Hefei University of Technology); Le Wu (Hefei University of Technology); Meng Wang (Hefei University of Technology)
• Mention Recommendation for Multimodal Microblog with Cross-attention Memory Network
  Renfeng Ma (Fudan University); Qi Zhang (Fudan University); Jiawen Wang (Fudan University); Lizhen Cui (Shandong Univerisity); Xuanjing Huang (Fudan University)
• Learning Geo-Social User Topical Profiles with Bayesian Hierarchical User Factorization
  Haokai Lu (Texas A&M University); Wei Niu (Texas A&M University); James Caverlee (Texas A&M University)
• A neural network approach to jointly modeling social networks and mobile trajectories (TOIS)
  Cheng Yang (Tsinghua University), Maosong Sun (Tsinghua University), Wayne Xin Zhao (Renmin University of China), Zhiyuan Liu (Tsinghua University), Edward Y. Chang (HTC Research)

Session 2C: App Search & Recommendation
July 9 (Monday), 13:30 – 15:00, Michigan (Floor 2)
Chair: Eugene Agichtein (Emory University)

• Target Apps Selection: Towards a Unified Search Framework for Mobile Devices
  Mohammad Aliannejadi (Università della Svizzera italiana); Hamed Zamani (University of Massachusetts Amherst); Fabio Crestani (Università della Svizzera italiana); W. Bruce Croft (University of Massachusetts Amherst)
• Mining exploratory behavior to improve mobile app recommendation (TOIS)
  Jiangning He (Tsinghua University), Hongyan Liu (Tsinghua University)
• Cross-platform app recommendation by jointly modeling rating and texts (TOIS)
  Da Cao (Xiamen University), Xiangnan He (National University of Singapore), Liqiang Nie (Shandong University), Xiaochi Wei (Beijing Institute of Technology), Xia Hu (Texas A&M), Shunxiang Wu (Xiamen University), Tat-Seng Chua (National University of Singapore)
• Version-aware rating prediction for mobile app recommendation (TOIS)
  Yuan Yao (Nanjing University), Wayne Xin Zhao (Renmin University of China), Yaojing Wang (Nanjing University), Hanghang Tong (Arizona State University), Feng Xu (Nanjing University), Jian Lu (Nanjing University)

Session 2D: Conversational Systems
July 9 (Monday), 13:30 – 15:00, Mendelssohn Theatre
Chair: Jian-Yun Nie (University of Montreal)

• Dialogue Act Recognition via CRF-Attentive Structured Network
  Zheqian Chen (Zhejiang University); Rongqin Yang (Zhejiang University); Zhou Zhao (Zhejiang University); Deng Cai (Zhejiang University); Xiaofei He (Zhejiang University)
• Conversational Recommender System
  Yueming Sun (University of California, Santa Cruz); Yi Zhang (University of California, Santa Cruz)
• Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems
  Liu Yang (University of Massachusetts Amherst); Minghui Qiu (Alibaba Group); Chen Qu (University of Massachusetts Amherst); Jiafeng Guo (Institute of Computing Technology); Yongfeng Zhang (Rutgers University); Bruce Croft (University of Massachusetts Amherst); Jun Huang (Alibaba Group); Haiqing Chen (Alibaba Group)
• Chat More: Deepening and Widening the Chatting Topic via A Deep Model
  Wenjie Wang (Shandong University); Minlie Huang (Tsinghua University); Xin-Shun Xu (Shandong University); Fumin Shen (University of Electronic Science and Technology of China); Liqiang Nie (Shandong University)

Poster and Demo Reception 1
July 9 (Monday), 15:30 – 17:00, Ballroom (Floor 2)

 Short Papers

• Pytrec_eval: An Extremely Fast Python Interface to trec_eval
• Split-Lists and Initial Thresholds for WAND-based Search
• Ontology Evaluation with Path-based Text-aware Entropy Computation
• Reducing Variance in Gradient Bandit Algorithm using Antithetic Variates Method
• A Flexible Forecasting Framework for Hierarchical Time Series with Seasonal Patterns: A Case Study of Web Traffic
• Query Performance Prediction using Passage Information
• Users, Adaptivity, and Bad Abandonment
• Knowledge-aware Attentive Neural Network for Ranking Question Answer Pairs
• A Living Lab Study of Query Amendment in Job Search
• Attention-driven Factor Model for Explainable Personalized Recommendation
• IRevalOO: An Object Oriented Framework for Retrieval Evaluation
• Translating Representations of Knowledge Graphs with Neighbors
• Index Compression for BitFunnel Query Processing
• Large-Scale Image Retrieval with Elasticsearch
• A Co-Memory Network for Multimodal Sentiment Analysis
• Investigating User Perception of Gender Bias in Image Search
• Killing Two Birds With One Stone: Concurrent Ranking of Tags and Comments of Social Images
• Imagination Based Sample Construction for Zero-Shot Learning
• Parameterizing Kterm Hashing
• Technology Assisted Reviews: Finding the Last Few Relevant Documents by Asking Yes/No Questions to Reviewers
• An Information Retrieval Framework for Contextual Suggestion Based on Heterogeneous Information Network Embeddings
• Toward an Interactive Patent Retrieval Framework based on Distributed Representations
• Consistency and Variation in Kernel Neural Ranking Model
• Review Sentiment-Guided Scalable Deep Recommender System
• Learning to Detect Pathogenic Microorganism of Community-acquired Pneumonia
• Towards Distributed Pairwise Ranking using Implicit Feedback
• Semantic Location in Email Query Suggestion
• GraphCAR: Content-aware Multimedia Recommendation with Graph Autoencoder
• Multi-level Abstraction Convolutional Model with Weak Supervision for Information Retrieval
• Analyzing and Characterizing User Intent in Information-seeking Conversations
• Modeling Multidimensional User Relevance in IR using Vector Spaces
• Are we on the Right Track? An Examination of Information Retrieval Methodologies
• Fine-Grained Information Identification in Health Related Posts
• Quantitative Information Extraction From Social Data
• Measuring Influence on Instagram: a Network-Oblivious Approach
• Event2Vec: Neural Embeddings for News Events
• Universal Approximation Functions for Fast Learning to Rank
• Modeling Mobile User Actions for Purchase Recommendation using Deep Memory Networks
• Cross Domain Regularization for Neural Ranking Models using Adversarial Learning
• Affective Representations for Sarcasm Detection
• A User Study on Snippet Generation: Text Reuse vs. Paraphrases
• New Embedded Representations and Evaluation Protocols for Inferring Transitive Relations
• Taxi or Hitchhiking: Predicting Passenger’s Preferred Service on Ride Sharing Platforms
• Towards Intent-Aware Contextual Music Recommendation: Initial Experiments
• Deep Domain Adaptation Based on Multi-layer Joint Kernelized Distance
• Do Not Pull My Data for Resale: Protecting Data Providers using Data Retrieval Pattern Analysis
• K-plet Recurrent Neural Networks for Sequential Recommendation
• Citation Worthiness of Sentences in Scientific Reports

 Demos

• SearchX: Empowering Collaborative Search Research
• A/B Testing with APONE
• CoNEREL: Collective Information Extraction in News Articles
• A2A: Benchmark Your Clinical Decision Support Search
• An Information Retrieval Experiment Framework for Domain Specific Applications
• LogCanvas: Visualizing Search History Using Knowledge Graphs
• API Caveat Explorer: Surfacing Negative Usages from Practice
• SmartTable: A Spreadsheet Program with Intelligent Assistance

Session 3A: Social Good
10 July (Tuesday), 10:30 – 12:00, Hussey (Floor 2)
Chair: David Carmel (Amazon Research)

• Identifying Sub-events and Summarizing Disaster-Related Information from Microblogs
  Koustav Rudra (Indian Institute of Technology Kharagpur, India); Pawan Goyal (Indian Institute of Technology Kharagpur, India); Niloy Ganguly (Indian Institute of Technology Kharagpur, India); Prasenjit Mitra (The Pennsylvania State University, University Park, PA, USA); Muhammad Imran (Qatar Computing Research Institute (HBKU), Doha, Qatar)
• The Rise of Guardians: Fact-checking URL Recommendation to Combat Fake News
  Nguyen Vo (Worcester Polytechnic Institute); Kyumin Lee (Worcester Polytechnic Institute)
• DeepMob: Learning Deep Knowledge of Human Emergency Behavior and Mobility from Big and Heterogeneous Data Sources (TOIS)
  Xuan Song (University of Tokyo), Ryosuke Shibasaki (University of Tokyo), Nicholos Jing Yuan (Microsoft Research), Xing Xie (Microsoft Research), Tao Li (Florida Intl. University and Nanjing University), Ryutaro Adachi (Zenrin DataCom Co.)

Session 3B: Privacy
10 July (Tuesday), 10:30 – 12:00, Vanderberg (Floor 2)
Chair: Grace Hui Yang (Georgetown University)

• Intent-aware Query Obfuscation for Privacy Protection in Personalized Web Search
  Wasi Uddin Ahmad (UC Los Angeles); Kai-Wei Chang (UC Los Angeles); Hongning Wang (University of Virginia)
• A Personal Privacy Preserving Framework: I Let You Know Who Can See What
  Xuemeng Song (Shandong University); Xiang Wang (National University of Singapore); Liqiang Nie (Shandong University); Xiangnan He (National University of Singapore); Zhumin Chen (Shandong University); Wei Liu (Tencent AI Lab)
• SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining
  Benjamin Weggenmann (SAP SE); Florian Kerschbaum (University of Waterloo)
• Privacy-aware Ranking with Tree Ensembles on the Cloud
  Shiyu Ji (University of California, Santa Barbara); Daniel Agun (University of California, Santa Barbara); Jinjin Shao (University of California, Santa Barbara); Tao Yang (University of California, Santa Barbara)

Session 3C: Question Answering
July 10 (Tuesday), 10:30 – 12:00, Michigan (Floor 2)
Chair: Jianfeng Gao (Microsoft Research)

• Multihop Attention Networks for Question Answer Matching
  Nam Khanh Tran (L3S Research Centre); Claudia Niederée (L3S Research Centre)
• Ranking Documents by Answer-Passage Quality
  Evi Yulianti (RMIT University); Ruey-Cheng Chen (RMIT University); Falk Scholer (RMIT University); Bruce Croft (University of Massachusetts Amherst); Mark Sanderson (RMIT University)
• Characterizing and Supporting Question Answering in Human-to-Human Communication
  Xiao Yang (The Pennsylvania State University); Ahmed Hassan Awadallah (Microsoft); Madian Khabsa (Apple); Wei Wang (Microsoft); Miaosen Wang (Microsoft)

Session 3D: Learning to Rank II
July 10 (Tuesday), 10:30 – 12:00, Mendelssohn Theatre
Chair: Jamie Callan (Carnegie Mellon University)

• Adversarial Personalized Ranking for Recommendation
  Xiangnan He (National University of Singapore); Zhankui He (Fudan University); Xiaoyu Du (University of Science and Technology of China); Tat-Seng Chua (National University of Singapore)
• Turning Clicks into Purchases: Revenue Optimization for Product Search in E-Commerce
  Liang Wu (Arizona State University); Diane Hu (Etsy); Liangjie Hong (Etsy Inc.); Huan Liu (Arizona State University)
• Modeling Diverse Relevance Patterns in Ad-hoc Retrieval
  Yixing Fan (ict); Jiafeng Guo (ict); Yanyan Lan (ict); Jun Xu (ict); Chengxiang Zhai (Department of Computer Science University of Illinois at Urbana-Champaign); Xueqi Cheng (ict)
• Fast ranking with additive ensembles of oblivious and non-oblivious regression trees (TOIS)
  Domenico Dato (Tiscali Italia S.p.A.), Claudio Lucchese (ISTI-CNR), Franco Maria Nardini (ISTI-CNR), Salvatore Orlando (Ca’ Foscari University of Venice), Raffaele Perego (ISTI-CNR), Nicola Tonellotto (ISTI-CNR), Rossano Venturini (University of Pisa)

Session 4A: Fairness & Robustness
July 10 (Tuesday), 13:30 – 15:00, Hussey (Floor 2)
Chair: Fernando Diaz (Spotify)

• Unbiased Learning to Rank with Unbiased Propensity Estimation
  Qingyao Ai (University of Massachusetts Amherst); Keping Bi (University of Massachusetts Amherst); Cheng Luo (Tsinghua University); Jiafeng Guo (Institute of Computing Technology, Chinese Academy of Sciences); W. Bruce Croft (University of Massachusetts Amherst)
• Ranking Robustness under Adversarial Document Manipulations
  Gregory Goren (Technion); Fiana Raiber (Yahoo Research); Moshe Tennenholtz (Technion); Oren Kurland (Technion)
• Equity of Attention: Amortizing Individual Fairness in Rankings
  Asia J. Biega (Max Planck Institute for Informatics); Krishna P. Gummadi (MPI-SWS); Gerhard Weikum (Max Planck Institute for Informatics)
• Should I Follow the Crowd? A Probabilistic Analysis of the Effectiveness of Popularity in Recommender Systems
  Rocío Cañamares (Universidad Autónoma de Madrid); Pablo Castells (Universidad Autónoma de Madrid)

Session 4B: Behavior
July 10 (Tuesday), 13:30 – 15:00, Vandenberg (Floor 2)
Chair: Diane Kelly (University of Tennessee)

• Constructing an Interaction Behavior Model for Web Image Search
  Xiaohui Xie (Tsinghua University); Jiaxin Mao (Tsinghua University); Maarten de Rijke (University of Amsterdam); Ruizhe Zhang (Tsinghua University); Min Zhang (Tsinghua University); Shaoping Ma (Tsinghua University)
• Between Clicks and Satisfaction: Study on Multi-Phase User Preferences and Satisfaction for Online News Reading
  Hongyu Lu (Tsinghua University); Min Zhang (Tsinghua University); Shaoping Ma (Tsinghua University)
• The effects of manipulating task determinability on search behaviors and outcomes
  Robert Capra (The University of North Carolina at Chapel Hill); Jaime Arguello (The University of North Carolina at Chapel Hill); Heather O’Brien (The University of British Columbia); Yuan Li (The University of North Carolina at Chapel Hill); Bogeum Choi (The University of North Carolina at Chapel Hill)
• The effects of aggregated search coherence on search behavior (TOIS)
  Jaime Arguello (Univ. of North Carolina at Chapel Hill), Rob Capra (Univ. of North Carolina at Chapel Hill)

Session 4C: Medical & Legal IR
July 10 (Tuesday), 13:30 – 15:00, Michigan (Floor 2)
Chair: Isabelle Moulinier (Capital One)

• Seed-driven Document Ranking for Systematic Reviews in Evidence-Based Medicine
  Grace E. Lee (Nanyang Technological University); Aixin Sun (Nanyang Technological University)
• A Dataset and an Examination of Identifying Passages for Due Diligence
  Adam Roegiest (Kira Systems); Alexander Hudek (Kira Systems); Anne McNulty (Kira Systems)
• Generating Better Queries for Systematic Reviews
  Harrisen Scells (Queensland University of Technology); Guido Zuccon (Queensland University of Technology)
• Modeling Dynamic Pairwise Attention for Crime Classification over Legal Articles
  Pengfei Wang (Beijing University of Posts and Telecommunications); Ze Yang (Beijing University of Post and Telecommunications); Shu Zi (Chinese Academy of Science); Yongfeng Zhang (Rutgers University); Lei Zhang (Beijing University of Post and Telecommunications); Shaozhang Niu (Beijing University of Post and Telecommunications)

Session 4D: Recommender Systems – Methods
July 10 (Tuesday), 13:30 – 15:00, Mendelssohn Theatre
Chair: Jun Xu (Chinese Academy of Sciences)

• Learning Contextual Bandits in a Non-stationary Environment
  Qingyun Wu (University of Virginia); Naveen Iyer (University of Virginia); Hongning Wang (University of Virginia)
• Improving Sequential Recommendation with Knowledge-enhanced Memory Networks
  Jin Huang (School of Information, Renmin University of China); Wayne Xin Zhao (School of Information, Renmin University of China); Hongjian Dou (School of Information, Renmin University of China); Ji-Rong Wen (School of Information, Renmin University of China); Edward Y. Chang (Research & Innovation, HTC)
• Collaborative Memory Network for Recommendation Systems
  Travis Ebesu (Santa Clara University); Bin Shen (Google); Yi Fang (Santa Clara University)
• Streaming Ranking Based Recommender Systems
  Weiqing Wang (The University of Queensland); Hongzhi Yin (The University of Queensland); Zi Huang (The University of Queensland); Qinyong Wang (The University of Queensland); Xingzhong Du (The University of Queensland); Quoc Viet Hung Nguyen (Griffith University)

Poster and Demo Reception 2
July 10 (Tuesday), 15:30 – 17:00, Ballroom (Floor 2)

Short Papers

• Ad Click Prediction in Sequence with Long Short-Term Memory Networks: An Externality-aware Model
• Assessing the Readability of Web Search Results for Searchers with Dyslexia
• Comparing Two Binned Probability Distributions for Information Access Evaluation
• Robust Asymmetric Recommendation via Min-Max Optimization
• From the PRP to the Low Prior Discovery Recall Principle for Recommender Systems
• Deep Learning for Epidemiological Predictions
• Query Variation Performance Prediction for Systematic Reviews
• Attention-based Hierarchical Neural Query Suggestion
• Texygen: A Benchmarking Platform for Text Generation Models
• CA-LSTM: Search Task Identification with Context Attention based LSTM
• On the Volatility of Commercial Search Engines and its Impact on Information Retrieval Research
• Deep Semantic Text Hashing with Weak Supervision
• Who is the Mr. Right for Your Brand? — Discovering Brand Key Assets via Multi-modal Asset-aware Projection
• Sogou-QCL: A New Dataset with Click Relevance Label
• Towards Designing Better Session Search Evaluation Metrics
• Predicting Contradiction Intensity: Low, Strong or Very Strong?
• A Large-Scale Study of Mobile Search Examination Behavior
• Ranking Without Learning: Towards Historical Relevance-based Ranking of Social Images
• Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate
• How Much is Too Much? Whole Session vs. First Query Behaviors in Task Type Prediction
• Effectiveness Evaluation with a Subset of Topics: A Practical Approach
• Locality-adapted Kernel Densities for Tweet Localization
• Related or Duplicate: Distinguishing Similar CQA Questions via Convolutional Neural Networks
• Procrastination is the Thief of Time: Evaluating the Effectiveness of Proactive Search Systems
• Convolution-based Memory Network for Aspect-based Sentiment Analysis
• WikiPassageQA: A Benchmark Collection for Research on Non-factoid Answer Passage Retrieval
• Beyond Pooling
• Testing the Cluster Hypothesis with Focused and Graded Relevance Judgments
• Query Performance Prediction Focused on Summarized Letor Features
• A Study of Per-Topic Variance on System Comparison
• Online Job Search: Study of Users’ Search Behavior using Search Engine Query Logs
• Identifying and Modeling Information Resumption Behaviors in Cross-Device Search
• Optimizing Query Evaluations Using Reinforcement Learning for Web Search
• SAAN: A Sentiment-Aware Attention Network for Sentiment Analysis
• An Attribute-aware Neural Attentive Model for Next Basket Recommendation
• Characterizing Question Facets for Complex Answer Retrieval
• A Test Collection for Coreferent Mention Retrieval
• What Do Users Say to Their TVs? An Analysis of Voice Queries to Entertainment Systems
• Sanity Check: A Strong Alignment and Information Retrieval Baseline for Question Answering
• Explaining Controversy on Social Media via Stance Summarization
• Identifying Clickbait: A Multi-Strategy Approach Using Neural Networks
• Multi-Target Stance Detection via a Dynamic Memory-Augmented Network
• Query Performance Prediction and Effectiveness Evaluation Without Relevance Judgments: Two Sides of the Same Coin
• A New Term Frequency Normalization Model for Probabilistic Information Retrieval
• Transparent Tree Ensembles
• A Taxonomy of Queries for E-commerce Search
• Theoretical Analysis of Interdependent Constraints in Pseudo-Relevance Feedback
• Unsupervised Cross-Lingual Information Retrieval Using Monolingual Data Only
• Toward Voice Query Clarification
• A Test Collection for Evaluating Legal Case Law Search

Demos

• Interactive Symptom Elicitation for Diagnostic Information Retrieval
• Sover! Social Media Observer
• Combining Terrier with Apache Spark to create Agile Experimental Information Retrieval Pipelines
• Dynamic Composition of Question Answering Pipelines with Frankenstein
• A System for Efficient High-Recall Retrieval
• HyPlag: A Hybrid Approach to Academic Plagiarism Detection
• RecAdvisor: Criteria-based Ph.D. Supervisor Recommendation
• Minority Report by Lemur: Supporting Search Engine with Virtual Reality
• Hide-n-Seek: An Intent-aware Privacy Protection Plugin for Personalized Web Search
• Vote Goat: Conversational Movie Recommendation

Session 5A: Location and Trajectory
July 11 (Wednesday), 9:00 – 10:30, Hussey (Floor 2)
Chair: Dawei Yin (JD.com)

• Torch: A Search Engine for Trajectory Data
  Sheng Wang (RMIT University); Zhifeng Bao (RMIT University); J. Shane Culpepper (RMIT University); Zizhe Xie (Nanjing University); Qizhi Liu (Nanjing University); Xiaolin Qin (Nanjing University of Aeronautics and Astronautics)
• Trip recommendation meets real-world constraints (TOIS)
  Chenyi Zhang (Simon Fraser University), Hongwei Liang (Simon Fraser University), Ke Wang (Simon Fraser University)
• Top-k Route Search through Submodularity Modeling of Recurrent POI Features
  Hongwei Liang (Simon Fraser University); Ke Wang (Simon Fraser University)
• Contextual Attention Recurrent Architecture for Context-Aware Venue Recommendation
  Jarana Manotumruksa (University of Glasgow); Craig Macdonald (University of Glasgow); Iadh Ounis (University of Glasgow)

Session 5B: Entities
July 11 (Wednesday), 9:00 – 10:30, Vandenberg (Floor 2)
Chair: Arjen de Vries (Radboud University)

• Entity Set Search of Scientific Literature: An Unsupervised Ranking Approach
  Jiaming Shen (University of Illinois at Urbana-Champaign); Jinfeng Xiao (University of Illinois at Urbana-Champaign); Xinwei He (University of Illinois at Urbana-Champaign); Jingbo Shang (University of Illinois at Urbana-Champaign); Saurabh Sinha (University of Illinois at Urbana-Champaign); Jiawei Han (University of Illinois at Urbana-Champaign)
• Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling
  Chenyan Xiong (Carnegie Mellon University); Zhengzhong Liu (Carnegie Mellon University); Jamie Callan (Carnegie Mellon University); Tie-Yan Liu (Microsoft)
• Automated Comparative Table Generation for Facilitating Human Intervention in Multi-Entity Resolution
  Jiacheng Huang (Nanjing University); Wei Hu (Nanjing University); Haoxuan Li (Nanjing University); Yuzhong Qu (Nanjing University)
• On-the-fly Table Generation
  Shuo Zhang (University of Stavanger); Krisztian Balog (University of Stavanger)

Session 5C: New Metrics
July 11 (Wednesday), 9:00 – 10:30, Michigan (Floor 2)
Chair: Tetsuya Sakai (Waseda University)

• Measuring the Utility of Search Engine Result Pages
  Leif Azzopardi (University of Strathclyde); Paul Thomas (Microsoft); Nick Craswell (Microsoft)
• How Well do Offline and Online Evaluation Metrics Measure User Satisfaction in Web Image Search?
  Fan Zhang (Tsinghua University); Ke Zhou (University of Nottingham); Yunqiu Shao (Tsinghua University); Cheng Luo (Tsinghua University); Min Zhang (Tsinghua University); Shaoping Ma (Tsinghua University)
• An Axiomatic Analysis of Diversity Evaluation Metrics: Introducing the Rank-Biased Utility Metric
  Enrique Amigó (UNED); Damiano Spina (RMIT University); Jorge Carrillo-De-Albornoz (UNED)
• Incorporating user expectation and behavior into the measurement of search effectiveness (TOIS)
  Alistair Moffat (University of Melbourne), Peter Bailey (Microsoft), Falk Scholer (RMIT University), Paul Thomas (Microsoft)

Session 5D: Recommender Systems – Applications
July 11 (Wednesday), 9:00 – 10:30, Mendelssohn Theatre
Chair: Yi Zhang (University of California Santa Cruz)

• Cross-language Citation Recommendation via Hierarchical Representation Learning on Heterogeneous Graph
  Zhuoren Jiang (Sun Yat-sen University); Yue Yin (Beijing Normal University); Liangcai Gao (Peking University); Yao Lu (Sun Yat-sen University); Xiaozhong Liu (Alibaba Group)
• Attentive Group Recommendation
  Da Cao (Hunan University); Xiangnan He (National University of Singapore); Lianhai Miao (Hunan University); Yahui An (University of Electronic Science and Technology of China); Chao Yang (Hunan University); Richang Hong (Hefei University of Technology)
• Calendar-Aware Proactive Email Recommendation
  Qian Zhao (University of Minnesota); Paul Bennett (Microsoft); Adam Fourney (Microsoft); Anne Thompson (Microsoft); Shane Williams (Microsoft); Adam D. Troy (Microsoft); Susan Dumais (Microsoft)
• Structuring Wikipedia Articles with Section Recommendations
  Tiziano Piccardi (Ecole Polytechnique Fédérale de Lausanne); Michele Catasta (Stanford University); Leila Zia (Wikimedia Foundation); Robert West (Ecole Polytechnique Fédérale de Lausanne)

Session 6A: Evaluation
July 11 (Wednesday), 11:00 – 12:30, Hussey (Floor 2)
Chair: Mark Sanderson (RMIT University)

• On Fine-Grained Relevance Scales
  Kevin Roitero (University of Udine); Eddy Maddalena (University of Southampton); Gianluca Demartini (The University of Queensland); Stefano Mizzaro (University of Udine)
• Automatic Ground Truth Expansion for Timeline Evaluation
  Richard Mccreadie (University of Glasgow); Craig Macdonald (University of Glasgow); Iadh Ounis (University of Glasgow)
• Stochastic Simulation of Test Collections: Evaluation Scores
  Julián Urbano (Delft University of Technology); Thomas Nagler (Technical University of Munich)
• Offline Comparative Evaluation with Incremental, Minimally-Invasive Online Feedback
  Ben Carterette (University of Delaware); Praveen Chandar (Spotify Research)

Session 6B: Hashing & Embedding
July 11 (Wednesday), 11:00 – 12:30, Vanderberg (Floor 2)
Chair: Nick Craswell (Microsoft)

• BiNE: Bipartite Network Embedding
  Ming Gao (East China Normal University); Leihui Chen (East China Normal University); Xiangnan He (National University of Singapore); Aoying Zhou (East China Normal University)
• Deep Domain Adaptation Hashing with Adversarial Learning
  Fuchen Long (University of Science and Technology of China); Ting Yao (Microsoft); Qi Dai (Microsoft); Xinmei Tian (University of Science and Technology of China); Jiebo Luo (University of Rochester); Tao Mei (Microsoft)
• Fast Scalable Supervised Hashing
  Xin Luo (Shandong University); Liqiang Nie (Shandong University); Xiangnan He (National University of Singapore); Ye Wu (Shandong University); Zhen-Duo Chen (Shandong University); Xin-Shun Xu (Shandong University)
• Hilbert Exclusion: Improved Metric Search Through Finite Isometric Embeddings (TOIS)
  Richard Connor (University of Strathclyde), Franco Alberto Cardillo (National Research Council of Italy – CNR), Lucia Vadicamo (National Research Council of Italy – CNR), Fausto Rabitti (National Research Council of Italy – CNR)

Session 6C: Knowledge bases/graphs
July 11 (Wednesday), 11:00 – 12:30, Michigan (Floor 2)
Chair: Krisztian Balog (University of Stavanger)

• Enriching Taxonomies With Functional Domain Knowledge
  Nikhita Vedula (The Ohio State University); Patrick K. Nicholson (Nokia Bell Labs); Deepak Ajwani (Nokia Bell Labs); Sourav Dutta (Nokia Bell Labs); Alessandra Sala (Nokia Bell Labs); Srinivasan Parthasarathy (The Ohio State University)
• On Link Prediction in Knowledge Bases: Max-K Criterion and Prediction Protocols
  Jiajie Mei (Beihang University); Richong Zhang (Beihang University); Yongyi Mao (University of Ottawa); Ting Deng (Beihang University)
• Weakly-supervised Contextualization of Knowledge Graph Facts
  Nikos Voskarides (University of Amsterdam); Edgar Meij (Bloomberg L.P.); Ridho Reinanda (Bloomberg L.P.); Abhinav Khaitan (Bloomberg L.P.); Miles Osborne (Bloomberg L.P.); Giorgio Stefanoni (Bloomberg L.P.); Prabhanjan Kambadur (Bloomberg L.P.); Maarten de Rijke (University of Amsterdam)

Session 6D: Mobile User Behavior
July 11 (Wednesday), 11:00 – 12:30, Mendelssohn Theatre
Chair: Makoto P. Kato (Kyoto University)

• Constructing Click Models for Mobile Search
  Jiaxin Mao (Tsinghua University); Cheng Luo (Tsinghua University); Min Zhang (Tsinghua University); Shaoping Ma (Tsinghua University)
• Update Delivery Mechanisms for Prospective Information Needs: An Analysis of Attention in Mobile Users
  Jimmy Lin (University of Waterloo); Salman Mohammed (University of Waterloo); Royal Sequiera (University of Waterloo); Luchen Tan (University of Waterloo)
• User modeling on Demographic attributes in big Mobile Social Networks (TOIS)
  Yuxiao Dong (University of Notre Dame), Nitesh V. Chawla (University of Notre Dame), Jie Tang (Tsinghua University), Yang Yang (Zhejiang University), Yang Yang (Northwestern University)
• Derive user preferences of mobile apps from their management activities (TOIS)
  Xuanzhe Liu (Peking University), Wei Ai (University of Michigan), Huoran Li (Peking University), Jian Tang (University of Michigan), Gang Huang (Peking University), Feng Feng (Wandoujia Lab), Qiaozhu Mei (University of Michigan)

Session 7A: Crowdsourcing & Assessment
July 11 (Wednesday), 14:30 – 15:40, Hussey (Floor 2)
Chair: Mark Smucker (University of Waterloo)

• Item Retrieval as Utility Estimation
  Shawn R. Wolfe (NASA); Yi Zhang (University of California, Santa Cruz)
• Crowd vs. Expert: What Can Relevance Judgment Rationales Teach Us About Assessor Disagreement?
  Mucahid Kutlu (Qatar University); Tyler McDonnell (The University of Texas at Austin); Yassmine Barkallah (Qatar University); Tamer Elsayed (Qatar University); Matthew Lease (The University of Texas at Austin)
• Curious Cart – Mobile context-aware conversational crowdsourcing knowledge acquisition (TOIS)
  Luka Bradeško (Jožef Stefan Institute and Jožef Stefan Postgraduate School), Michael Witbrock (IBM Thomas J Watson Research Center), Janez Starc (Jožef Stefan Institute and Jožef Stefan Postgraduate School), Zala Herga (Jožef Stefan Institute and Jožef Stefan Postgraduate School), Marko Grobelnik (Jožef Stefan Institute), Dunja Mladenić (Jožef Stefan Institute and Jožef Stefan Postgraduate School)

Session 7B: Content & Semantics
July 11 (Wednesday), 14:30 – 15:40, Vandernberg (Floor 2)
Chair: James Allan (University of Massachusetts Amherst)

• CAN: Enhancing Sentence Similarity Modeling with Collaborative and Adversarial Network
  Qin Chen (East China Normal University); Qinmin Hu (East China Normal University); Jimmy Huang (University of York); Liang He (East China Normal University)
• Identify Shifts of Word Semantics through Bayesian Surprise
  Zhuofeng Wu (Zhejiang University); Cheng Li (University of Michigan); Zhe Zhao (University of Michigan); Fei Wu (Zhejiang University); Qiaozhu Mei (University of Michigan)
• From Royals to Vegans: Characterizing Question Trolling on a Community Question Answering Website
  Ido Guy (Ben-Gurion University of the Negev & eBay Research); Bracha Shapira (Ben-Gurion University of the Negev)

Session 7C: Interfaces
July 11 (Wednesday), 14:30 – 15:40, Michigan (Floor 2)
Chair: Rob Capra (University of North Carolina at Chapel Hill)

• Ranking for Relevance and Display Preferences in Complex Presentation Layouts
  Harrie Oosterhuis (University of Amsterdam); Maarten de Rijke (University of Amsterdam)
• Natural Language Interfaces with Fine-Grained User Interaction: A Case Study on Web APIs
  Yu Su (University of California Santa Barbara); Ahmed Hassan Awadallah (Microsoft); Miaosen Wang (Microsoft); Ryen White (Microsoft)
• Search by screenshots for universal article clipping in mobile apps (TOIS)
  Kazutoshi Umemoto (Kyoto University), Ruihua Song (Microsoft Research Asia), Jian-Yun Nie (University of Montreal), Xing Xie (Microsoft Research Asia), Katsumi Tanaka (Kyoto University), Yong Rui (Microsoft Research Asia)

Future of IR Panel
July 11 (Wednesday), 16:10 – 17:15, Mendelssohn Theatre