The 11th ACM International Conference on Web Search and Data Mining

Los Angeles, California, USA, 2018.

Accepted Papers

This year, WSDM was able to accept 84 out of 514 papers, which amounts to an acceptance rate above 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 Email Overload
    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)
  • Economic Recommendation based on Pareto Efficient Resource Allocation
    Yongfeng Zhang (University of Massachusetts Amherst); Yi Zhang (University of California, Santa Cruz); Daniel Friedman (University of California, Santa Cruz)
  • Putting Data in the Driver's Seat: Optimizing Earnings for On-Demand Ridesharing
    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)

Spotlight Presentation

  • Topic Chronicle Forest for Topic Discovery and Tracking
    Noriaki Kawamae (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)
  • Bidirectional Active Learning with Human Training Based on Gold Instance Sampling
    Liang Qiao (Shanghai Jiao Tong University); Feilong Tang (Shanghai Jiao Tong University); Jiacheng Liu (Shanghai Jiao Tong 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 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)
  • 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)
  • 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)
  • Transformer: 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); Saurabh Tiwary (Microsoft); Nick Craswell (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)