Accepted Papers

This year, WSDM was able to accept 84 out of 514 papers, which amounts to an acceptance rate about 16%.

Full Presentation

• Cognitive Biases in Crowdsourcing
  Carsten Eickhoff (ETH Zurich)
• DSANLS: Accelerating Distributed Nonnegative Matrix Factorization via Sketching
  Yuqiu Qian (The University of Hong Kong); Conghui Tan (The Chinese University of Hong Kong); Nikos Mamoulis (University of Ioannina); David W. Cheung (The University of Hong Kong)
• Index Compression Using Byte-Aligned ANS Coding and Two-Dimensional Contexts
  Alistair Moffat (The University of Melbourne); Matthias Petri (The University of Melbourne)
• Ballpark Crowdsourcing: The Wisdom of Rough Group Comparisons
  Tom Hope (Hebrew University of Jerusalem); Dafna Shahaf (Hebrew University of Jerusalem)
• Micro Behaviors: A New Perspective in E-commerce Recommender Systems
  Meizi Zhou (JD.com); Zhuoye Ding (JD.com); Jiliang Tang (Michigan State University); Dawei Yin (JD.com)
• Leveraging Implicit Contribution Amounts to Facilitate Microfinancing Requests
  Suhas Ranganath (ASU); Ghazaleh Beigi (Arizona State University); Huan Liu (Arizona State University)
• OpenRec: A Modular Framework for Extensible and Adaptable Recommendation Algorithms
  Longqi Yang (Cornell Tech, Cornell University); Eugene Bagdasaryan (Cornell Tech, Cornell University); Joshua Gruenstein (Massachusetts Institute of Technology); Cheng-Kang Hsieh (Cornell Tech, Cornell University); Deborah Estrin (Cornell Tech, Cornell University)
• Modelling Domain Relationships for Transfer Learning on Chatbot-based Question Answering Systems
  Jianfei Yu (Singapore Management University); Minghui Qiu (Alibaba Group); Jing Jiang (Singapore Management University); Shuangyong Song (Alibaba Group); Jun Huang (Alibaba Group); Wei Chu (Alibaba Group); Haiqing Chen (Alibaba Group)
• Why People Search for Images using Web Search Engines
  Xiaohui Xie (Tsinghua University); Yiqun Liu (Tsinghua University); Maarten de Rijke (University of Amsterdam); Jiyin He (Centrum Wiskunde & Informatica (CWI)); Min Zhang (Tsinghua University); Shaoping Ma (Tsinghua University)
• Offline A/B testing for recommender systems
  Alexandre Gilotte (Criteo); Clement Calauzenes (Criteo); Thomas Nedelec (Criteo); Alexandre Abraham (Criteo); Simon Dollé (Criteo)
• Orienteering Algorithms for Generating Travel Itineraries
  Zachary Friggstad (University of Alberta); Sreenivas Gollapudi (Google); Kostas Kollias (Google); Tamas Sarlos (Google); Chaitanya Swamy (University of Waterloo); Andrew Tomkins (Google)
• Unsubscription: A Simple Way to Ease Overload in Email
  Iftah Gamzu (Amazon); Liane Lewin-Eytan (Amazon); Natalia Silberstein (Yahoo Research)
• Predicting Audio Advertisement Quality
  Samaneh Ebrahimi (Georgia Institute of Technology); Hossein Vahabi (Pandora Media Inc.); Matthew Prockup (Pandora Media Inc.); Oriol Nieto (Pandora Media Inc.)
• Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
  Jiezhong Qiu (Tsinghua University); Yuxiao Dong (Microsoft); Hao Ma (Microsoft); Jian Li (Tsinghua University); Kuansan Wang (Microsoft); Jie Tang (Tsinghua University)
• A Path-constrained Framework for Discriminating Substitutable and Complementary Products in E-commerce
  Zihan Wang (Data Science Lab, JD.com); Ziheng Jiang (Data Science Lab, JD.com); Zhaochun Ren (Data Science Lab, JD.com); Jiliang Tang (Michigan State University); Dawei Yin (Data Science Lab, JD.com)
• User Intent, Behaviour, and Perceived Satisfaction in Product Search
  Ning Su (Tsinghua University); Jiyin He (CWI); Yiqun Liu (Tsinghua University); Min Zhang (Tsinghua University); Shaoping Ma (Tsinghua University)
• Putting Data in the Driver's Seat: Optimizing Earnings for On-Demand Ride-Hailing
  Harshal Chaudhari (Boston University); John Byers (Boston University); Evimaria Terzi (Boston University)
• Combating Crowdsourced Review Manipulators: A Neighborhood-Based Approach
  Parisa Kaghazgaran (Texas A&M University); James Caverlee (Texas A&M University); Anna Squicciarini (The Pennsylvania State University)
• Latent Cross: Making Use of Context in Recurrent Recommender Systems
  Alex Beutel (Google); Paul Covington (Google); Sagar Jain (Google); Can Xu (Google); Jia Li (University of Illinois at Chicago); Vince Gatto (Google); Ed H. Chi (Google)
• Position Bias Estimation for Unbiased Learning to Rank in Personal Search
  Xuanhui Wang (Google); Nadav Golbandi (Google); Michael Bendersky (Google); Donald Metzler (Google); Marc Najork (Google)
• Identifying Informational vs. Conversational Questions on Community Question Answering Archives
  Ido Guy (eBay Research); Victor Makarenkov (Ben-Gurion University of the Negev); Niva Hazon (Ben-Gurion University of the Negev); Lior Rokach (Ben-Gurion University of the Negev); Bracha Shapira (Ben-Gurion University of the Negev)
• Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation
  Jooyeon Kim (Korea Advanced Institute of Science and Technology); Behzad Tabibian (Max Planck Institute for Intelligent Systems); Alice Oh (Korea Advanced Institute of Science and Technology); Bernhard Schölkopf (Max Planck Institute for Intelligent Systems); Manuel Gomez Rodriguez (Max Planck Institute for Software Systems)
• Joint Non-negative Matrix Factorization for Learning Ideological Leaning on Twitter
  Preethi Lahoti (Max Planck Institute for Informatics); Kiran Garimella (Aalto University); Aristides Gionis (Aalto University)

Spotlight Presentation

• Topic Chronicle Forest for Topic Discovery and Tracking
  Noriaki. K (The University of Tokyo)
• Exploring Expert Cognition for Attributed Network Embedding
  Xiao Huang (Texas A&M University); Qingquan Song (Texas A&M University); Jundong Li (Arizona State University); Xia Ben Hu (Texas A&M University)
• Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
  Jiaxi Tang (Simon Fraser University); Ke Wang (Simon Fraser University)
• Convolutional Neural Networks for Soft-Matching N-Grams in Ad-hoc Search
  Zhuyun Dai (Carnegie Mellon University); Chenyan Xiong (Carnegie Mellon University); Jamie Callan (Carnegie Mellon University); Zhiyuan Liu (Tsinghua University)
• Extreme Multi-label Learning with Label Features for Warm-start Tagging, Ranking & Recommendation
  Yashoteja Prabhu (IIT Delhi); Shilpa Gopinath (Samsung Research India); Kunal Dahiya (IIT Delhi); Anil Kag (Microsoft); Shrutendra Harsola (Microsoft IDC Bangalore); Rahul Agrawal (Microsoft IDC Bangalore); Manik Varma (Microsoft)
• Demographics and Dynamics of Mechanical Turk Workers
  Djellel Difallah (New York University); Elena Filatova (CUNY); Panos Ipeirotis (New York University)
• Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering
  Yi Tay (Nanyang Technological University); Anh Tuan Luu (Institute for Infocomm Research); Siu Cheung Hui (Nanyang Technological University)
• Bayesian Optimization for Optimizing Retrieval Systems
  Dan Li (University of Amsterdam); Evangelos Kanoulas (University of Amsterdam)
• SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction
  Hongwei Wang (Shanghai Jiao Tong University); Fuzheng Zhang (Microsoft); Min Hou (University of Science and Technology of China); Xing Xie (Microsoft); Minyi Guo (Shanghai Jiao Tong University); Qi Liu (USTC)
• A Unified Processing Paradigm for Interactive Location-based Web Search
  Sheng Wang (RMIT University); Zhifeng Bao (RMIT University); Shixun Huang (RMIT University); Rui Zhang (The University of Melbourne)
• Sequential Recommendation with User Memory Networks
  Xu Chen (Tsinghua University); Hongteng Xu (Georgia Institute of Technology); Yongfeng Zhang (University of Massachusetts Amherst); Yixin Cao (Tsinghua University); Zheng Qin (Tsinghua University); Jiaxi Tang (Simon Fraser University); Hongyuan Zha (Georgia Institute of Technology)
• Joint Generative-Discriminative Aggregation Model for Multi-Option Crowd labels
  Kamran Ghasedi Dizaji (University of Pittsburgh); Yanhua Yang (Xidian University); Heng Huang (University of Pittsburgh)
• Performance Analysis of a Privacy Constrained kNN Recommendation Using Data Sketches
  Armita Afsharinejad (Insight Centre for Data Analytics, University College Dublin); Neil Hurley (Insight Centre for Data Analytics, University College Dublin)
• Streaming Link Prediction on Dynamic Attributed Networks
  Jundong Li (Arizona State University); Kewei Cheng (Arizona State University); Liang Wu (Arizona State University); Huan Liu (Arizona State University)
• Robust Transfer Learning for Cross-domain Collaborative Filtering Using Multiple Rating Patterns Approximation
  Ming He (Faculty of Information Technology, Beijing University of Technology); Jiuling Zhang (Faculty of Information Technology, Beijing University of Technology); Peng Yang (Faculty of Information Technology, Beijing University of Technology); Kaisheng Yao (Faculty of Information Technology, Beijing University of Technology)
• Query Driven Algorithm Selection in Early Stage Retrieval
  Joel Mackenzie (RMIT University); J. Shane Culpepper (RMIT University); Roi Blanco (Amazon); Matt Crane (University of Waterloo); Charles L. A. Clarke (University of Waterloo); Jimmy Lin (University of Waterloo)
• Tracing Fake-News Footprints: Characterizing Social Media Messages by How They Propagate
  Liang Wu (Arizona State University); Huan Liu (Arizona State University)
• Peeling Bipartite Networks for Dense Subgraph Discovery
  Ahmet Erdem Sarıyüce (University at Buffalo); Ali Pinar (Sandia National Laboratories)
• Multidimensional network embedding with hierarchical structures
  Yao Ma (Michigan State University); Zhaochun Ren (Data Science Lab, JD.com); Ziheng Jiang (Data Science Lab, JD.com); Jiliang Tang (Michigan State University); Dawei Yin (Data Science Lab, JD.com)
• Predicting Multi-step Citywide Passenger Demands using Attention-based Neural Networks
  Xian Zhou (Shanghai Jiao Tong University); Yanyan Shen (Shanghai Jiao Tong University); Yanmin Zhu (Shanghai Jiao Tong University); Linpeng Huang (Dept. of Computer Science and Engineering, ShangHai Jiao Tong University)
• Modeling Time to Open of Emails with a Latent State for User Engagement Level
  Moumita Sinha (Adobe Research); Vishwa Vinay (Adobe Research); Harvineet Singh (Adobe Research)
• Can you Trust the Trend? Discovering Simpson's Paradoxes in Social Data
  Nazanin Alipourfard (University of Southern California Information Sciences Institute); Peter Fennell (University of Southern California Information Sciences Institute); Kristina Lerman (University of Southern California Information Sciences Institute)
• Discrete Deep Learning for Fast Content-Aware Recommendation
  Yan Zhang (University of Electronic Science and Technology of China); Hongzhi Yin (The University of Queensland); Zi Huang (The University of Queensland); Xingzhong Du (The University of Queensland); Guowu Yang (University of Electronic Science and Technology of China); Defu Lian (University of Electronic Science and Technology of China)
• ERM-PACRR: A Neural IR model with Enhanced Relevance Matching
  Kai Hui (Max Planck Institute for Informatics); Andrew Yates (Max Planck Institute for Informatics); Klaus Berberich (Max Planck Institute for Informatics); Gerard de Melo (Rutgers University)
• Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction
  Ziniu Hu (Peking University); Weiqing Liu (Microsoft); Jiang Bian (Microsoft); Xuanzhe Liu (Peking University); Tie-Yan Liu (Microsoft)
• User Profiling through Deep Multimodal Fusion
  Golnoosh Farnadi (University of California Santa Cruz); Jie Tang (Tsinghua University); Martine De Cock (University of Washington); Marie-Francine Moens (KU Leuven)
• CrossFire: Cross Media Joint Friend and Item Recommendations
  Kai Shu (Arizona State University); Suhang Wang (Arizona State University); Jiliang Tang (Michigan State University); Yilin Wang (Arizona State University); Huan Liu (Arizona State University)
• VISIR: Visual and Semantic Image Label Refinement
  Sreyasi Nag Chowdhury (Max Planck Institute for Informatics); Niket Tandon (Allen Institute for AI); Hakan Ferhatosmanoglu (University of Warwick); Gerhard Weikum (Max Planck Institute for Informatics)
• Sketch 'Em All: Approximate Similarity Search for Dynamic Data Streams
  Marc Bury (Thyssenkrupp Industrial Solutions AG); Chris Schwiegelshohn (Sapienza University of Rome); Mara Sorella (Sapienza University of Rome)
• Improving Negative Sampling for Word Representation using Self-embedded Features
  Long Chen (University of Glasgow); Fajie Yuan (University of Glasgow); Joemon Jose (University of Glasgow); Weinan Zhang (Shanghai Jiao Tong University)
• Shortcutting Label Propagation for Distributed Connected Components
  Stergios Stergiou (Yahoo Research); Dipen Rughwani (Yahoo Research); Kostas Tsioutsiouliklis (Yahoo Research)
• Consistent Transformation of Ratio Metrics for Efficient Online Controlled Experiments
  Roman Budylin (Yandex); Alexey Drutsa (Yandex); Ilya Katsev (Yandex); Valeriya Tsoy (Yandex)
• Short-Term Satisfaction and Long-Term Coverage: Understanding How Users Tolerate Algorithmic Exploration
  Tobias Schnabel (Cornell University); Paul Bennett (Microsoft); Susan Dumais (Microsoft); Thorsten Joachims (Cornell University, Dept. of Computer Science)
• A Discrete Choice Model for Subset Selection
  Austin Benson (Cornell University); Ravi Kumar (Google); Andrew Tomkins (Google)
• Dynamic Word Embeddings for Evolving Semantic Discovery
  Zijun Yao (Rutgers University); Yifan Sun (Technicolor Research); Weicong Ding (Amazon); Nikhil Rao (Amazon); Hui Xiong (Rutgers University)
• FACH: Fast Algorithm for Detecting Cohesive Hierarchies of Communities in Large Networks
  Mojtaba Rezvani (Australian National University); Qing Wang (Australian National University); Weifa Liang (Australian National University)
• Who Will Share My Image? Predicting the Content Diffusion Path in Online Social Networks
  Wenjian Hu (UC Davis); Krishna Kumar Singh (UC Davis); Fanyi Xiao (UC Davis); Jinyoung Han (Hanyang University); Chen-Nee Chuah (UC Davis); Yong Jae Lee (UC Davis)
• Customer Purchase Behavior Prediction from Payment Datasets
  Yu-Ting Wen (National Chiao Tung University); Wen-Chih Peng (National Chiao Tung University); Pei-Wen Yeh (National Chiao Tung University); Hong-Han Shuai (National Chiao Tung University)
• Inferring Dockless Shared Bike Distribution in New Cities
  Zhaoyang Liu (Shanghai Jiao Tong University); Yanyan Shen (Shanghai Jiao Tong University); Yanmin Zhu (Shanghai Jiao Tong University)
• Indirect Supervision for Relation Extraction using Question-Answer Pairs
  Zeqiu Wu (University of Illinois at Urbana-Champaign); Xiang Ren (University of Illinois at Urbana-Champaign); Frank F. Xu (Shanghai Jiao Tong University); Ji Li (University of Illinois at Urbana-Champaign); Jiawei Han (University of Illinois at Urbana-Champaign)
• Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning
  Meng Qu (University of Illinois at Urbana-Champaign); Jian Tang (HEC Montreal & Montreal Institute of Learning Algorithms); Jiawei Han (University of Illinois at Urbana-Champaign)
• Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction
  Mingming Sun (Baidu Research); Xu Li (Baidu Research); Xin Wang (Baidu Research); Miao Fan (Baidu Research); Yue Feng (Baidu Research); Ping Li (Baidu Research)
• Learning to Rank Personal Photos for Public Sharing
  Ido Guy (Ben-Gurion University of the Negev); Alexander Nus (eBay); Dan Pelleg (Yahoo Research); Idan Szpektor (Google)
• Recommendation in Heterogeneous Information Networks Based on Generalized Random Walk Model and Bayesian Personalized Ranking
  Zhengshen Jiang (Peking University); Hongzhi Liu (Peking University); Bin Fu (Peking University); Zhonghai Wu (Peking University); Tao Zhang (Beijing Huapinborui Network Technology Company)
• Web Search of Fashion Items with Multimodal Querying
  Katrien Laenen (KU Leuven); Susana Zoghbi (KU Leuven); Marie-Francine Moens (KU Leuven)
• Review-Aware Answer Prediction for Product-Related Questions Incorporating Aspects
  Qian Yu (The Chinese University of Hong Kong); Wai Lam (The Chinese University of Hong Kong)
• Fast Coreset-Based Max-Sum Diversity under Matroid Constraints
  Matteo Ceccarello (DEI - Università di Padova); Andrea Pietracaprina (DEI - Università di Padova); Geppino Pucci (DEI - Università di Padova, Italy)
• Fusing Diversity in Recommendations in Heterogeneous Information Networks
  Sharad Nandanwar (Department of Computer Science & Automation, Indian Institute of Science); Aayush Moroney (Indian Institute of Science); Narasimha Murty Musti (Indian Institute of Science)
• Fast and Scalable Distributed Loopy Belief Propagation on Real-World Graphs
  Saehan Jo (Seoul National University); Jaemin Yoo (Seoul National University); U Kang (Seoul National University)
• Collaborative Filtering Via Additive Ordinal Regression
  Jun Hu (Rutgers University); Ping Li (Rutgers University)
• Learning to Discover Domain-specific Web Content
  Kien Pham (New York University); Aecio Santos (New York University); Juliana Freire (New York University)
• Measuring the Latency of Depression Detection in Social Media
  Farig Sadeque (University of Arizona); Dongfang Xu (University of Arizona); Steven Bethard (University of Arizona)
• Neural Personalized Ranking for Image Recommendation
  Wei Niu (Texas A&M University); James Caverlee (Texas A&M University); Haokai Lu (Texas A&M University)
• Rev2: Fraudulent User Prediction in Rating Platforms
  Srijan Kumar (Stanford University); Bryan Hooi (CMU); Disha Makhija (Flipkart, India); Mohit Kumar (Flipkart); Christos Faloutsos (Carnegie Mellon University); V.S. Subrahmanian (Dartmouth College)
• Neural Ranking Models with Multiple Document Fields
  Hamed Zamani (University of Massachusetts Amherst); Bhaskar Mitra (Microsoft); Xia Song (Microsoft); Nick Craswell (Microsoft); Saurabh Tiwary (Microsoft)
• Neural Graph Learning: Training Neural Networks Using Graphs
  Thang Bui (University of Cambridge); Sujith Ravi (Google); Vivek Ramavajjala (Google)
• Deep Neural Architecture for Multi-Modal Retrieval based on Joint Embedding Space for Text and Images
  Saeid Balaneshinkordan (Wayne State University); Alexander Kotov (Wayne State University)
• sSketch: A Scalable Sketching Technique for PCA in the Cloud
  Md. Mehrab Tanjim (Bangladesh University of Engineering and Technology); Muhammad Abdullah Adnan (Bangladesh University of Engineering and Technology)