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
Wen-tau Yih Joshua Goodman Vitor R. Carvalho Qiaozhu Mei Chao Liu Hang Su ChengXiang Zhai Dou Shen Jian-Tao Sun Qiang Yang Zheng Chen Steven C. H. Hoi Rong Jin Michael R. Lyu Masashi Toyoda Masaru Kitsuregawa Christopher H. Brooks Nancy Montanez Qiankun Zhao Steven C. H. Hoi Tie-Yan Liu Sourav S Bhowmick Michael R. Lyu Wei-Ying Ma Chairs
PC Members
- Corin Anderson, (Google)
- Roberto Bayardo, (IBM Almaden Research Center)
- Ming-Syan Chen , (National Taiwan University )
- Byron Dom, (Yahoo! Inc.)
- Tina Eliassi-Rad, (Lawrence Livermore National Laboratory)
- Charles Elkan, (CSAIL, MIT)
- Ronen Feldman, (Bar-Ilan University)
- Rayid Ghani, (Accenture Technology Labs)
- David Gibson (IBM Almaden Research Center)
- Aristides Gionis, (University of Helsinki)
- Daniel Gruhl, (IBM Almaden Research Center)
- Ramanathan Guha, (Google)
- Thomas Hofmann, (Technical University of Darmstadt and Fraunhofer IPSI)
- Bing Liu, (University of Illinois at Chicago)
- Wei-Ying Ma, (Microsoft Research Asia)
- Shinichi Morishita, (University of Tokyo)
- Rajeev Motwani, (Stanford University)
- Ion Muslea, (Language Weaver, Inc.)
- Dmitry Pavlov, (Yahoo! Inc)
- Prabhakar Raghavan, (Yahoo! Inc)
- Raghu Ramakrishnan, (University of Wisconsin, Madison)
- Matthew Richardson, (Microsoft Research)
- Myra Spiliopoulou, (Otto-von-Guericke-University Magdeburg)
- Jaideep Srivastava, (University of Minnesota)
- Philip S. Yu, (IBM Watson Research Center)
- Osmar Zaiane, (University of Alberta)
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