Refereed Track: Data Mining

With the phenomenal growth of the Web, there is an ever-increasing volume of data and information being published in Web pages. The research in Web data mining aims to develop new techniques to effectively extract and mine useful knowledge/information from these Web sources. Due to the heterogeneity and the lack of structure of Web data, automated discovery of targeted or unexpected knowledge is a challenging task. It calls for novel methods that draw from a wide range of fields spanning data mining, machine learning, natural language processing, statistics, databases, and information retrieval.

For the data mining track, we invite original and high quality submissions addressing all aspects of Web data mining. The relevant topics include, but are not restricted to, the following:

• Classifying, clustering and recommending text/Web documents
• Mining Web content, link structure and usage data
• Building user profiles and providing recommendations
• Spatio-temporal analysis of blogs, reviews, discussions
• Change detection and monitoring Web pages/sites
• Entity and relationship extraction
• Schema and data integration, data cleaning
• Integrating linguistic and domain knowledge in Web mining
• Privacy preserving Web data mining

Accepted Papers

Chairs

• Ramakrishnan Srikant, Google Inc., USA (Vice Chair)
• Soumen Chakrabarti, IIT Bombay, India (Deputy Chair)

PC Members

• Ramakrishnan Srikant, Google Inc, (Vice Chair)
• Soumen Chakrabarti, IIT Bombay, India (Deputy Chair)
• Corin Anderson, Google Inc., USA
• Roberto Bayardo, IBM Almaden Research Center, USA
• Ming-Syan Chen, National Taiwan University, Taiwan
• Byron Dom, Yahoo! Inc., USA
• Tina Eliassi-Rad, Lawrence Livermore National Laboratory, USA
• Charles Elkan, CSAIL, MIT, USA
• Ronen Feldman, Bar-Ilan University, Israel
• Rayid Ghani, Accenture Technology Labs, USA
• David Gibson, IBM Almaden Research Center, USA
• Aristides Gionis, University of Helsinki, Finland
• Daniel Gruhl, IBM Almaden Research Center, USA
• Ramanathan Guha, Google Inc., USA
• Thomas Hofmann, Technical University of Darmstadt and Fraunhofer IPSI, Germany
• Bing Liu, University of Illinois at Chicago, USA
• Wei-Ying Ma, Microsoft Research Asia
• Shinichi Morishita, University of Tokyo, Japan
• Rajeev Motwani, Stanford University, USA
• Ion Muslea, Language Weaver, Inc., USA
• Dmitry Pavlov, Yahoo! Inc, USA
• Prabhakar Raghavan, Yahoo! Inc, USA
• Raghu Ramakrishnan, University of Wisconsin, Madison, USA
• Matthew Richardson, Microsoft Research
• Myra Spiliopoulou, Otto-von-Guericke-University Magdeburg, Germany
• Jaideep Srivastava, University of Minnesota, USA
• Philip S. Yu, IBM Watson Research Center, USA
• Osmar Zaiane, University of Alberta, Canada

Additional Reviewers

• Doug Beeferman
• Cliff Brunk
• Tim Converse
• Vuk Ercegovacs
• Shantanu Godbole
• Dmitry Leshchiner
• Kevin McCurley
• Taro L. Saito
• Dmitry Pavlovski
• Alexandrin Popescul
• Kunal Punera
• Ruofei Zhang