Web Mining

The multitude of rich information sources available on the Web today provides wonderful opportunities and challenges to Web mining for a diverse range of applications: constructing large knowledge bases, predicting the future, finding trends and epidemic in a population, marketing and recommendation, as well as filtering and cleaning Web content to improve the experience of users consuming it. This track covers data analysis for a wide variety of Web data including tweets, tags, links, logs, images, videos, and other multimodal data.
We welcome submissions of original high-quality research papers related to all aspects of Web Mining, including, but not limited to, the topics below.

  • Large-scale analysis of web data, including text, image, video, and metadata
  • Web measurements, evolution and models
  • Clustering, classification, and summarization of Web data
  • Multimodal Web content mining
  • Entity, event and relationship extraction from Web data
  • Data integration and data cleaning
  • Traffic and log analysis
  • Web mining for prediction and recommendation
  • Algorithms and systems for Web-scale mining
  • Learning representations and features from Web data
  • Novel Web mining applications

For questions related to this call, please email:

Area Chairs

  • Yizhou Sun, Northeastern University, USA
  • Yutaka Matsuo, University of Tokyo, Japan

Program Committee

  • Takuya Akiba, National Institute of Informatics
  • Azin Ashkan, Technicolor Labs
  • Timothy Baldwin, The University of Melbourne
  • Roberto Bayardo, Google Research
  • Michael Bendersky, Google, Inc.
  • Rui Cai, Microsoft Research, Asia
  • Qi He, LinkedIn
  • Xiangnan He, National University of Singapore
  • Liangjie Hong, Yahoo! Labs
  • Xia Hu, Texas A&M University
  • Adam Jatowt, Kyoto University
  • Akihiro Kishimoto, IBM
  • Arnd Christian König, Microsoft Research
  • Yehuda Koren, Google
  • Wai Lam, The Chinese University of Hong Kong
  • Hady Lauw, Singapore Management University
  • Chengkai Li, University of Texas at Arlington
  • Lei Liu, HP Labs
  • Huan Liu, Professor, Arizona State University
  • Michael Lyu, the Chinese University of Hong Kong
  • Hao Ma, Microsoft Research
  • Arjun Mukherjee, University of Houston
  • Olfa Nasraoui, University of Louisville
  • Alexandros Ntoulas, Zynga
  • Jian Pei, Simon Fraser University
  • Takeshi Sakaki, University of Tokyo
  • Tamas Sarlos, Google
  • H. Andrew Schwartz, University of Pennsylvania
  • Myra Spiliopoulou, Otto-von-Guericke-University Magdeburg
  • Chenhao Tan, Cornell University
  • Jian Tang, Microsoft Research Asia
  • Fujio Toriumi, University of Tokyo
  • Masashi Toyoda, University of Tokyo
  • Jianyong Wang, Tsinghua University
  • Hongning Wang, University of Virginia
  • Ke Wang, Simon Fraser University
  • Tim Weninger, University of Notre Dame
  • Jaewon Yang, Stanford University
  • Xiao Yu, Google Research
  • Philip Yu, University of Illinois at Chicago
  • Jeffery Xu Yu, Department of Systems Engineering & Engineering Management, Chinese University of Hong Kong
  • Zhe Zhao, University of Michigan, Ann Arbor
  • Feida Zhu, Singapore Management University
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