Thursday, July 22, 2010

Fourth ACM International Conference on Web Search and Data Mining (WSDM2011)

February 9-12, 2011, Hong Kong

http://www.wsdm2011.org/

Paper Submission Deadline: August 1, 2010
Workshop Proposal Deadline: July 25, 2010

WSDM (pronounced "wisdom") is the premier international ACM conference covering research in the areas of search and data mining on the Web. The 4th ACM WSDM Conference will take place in Hong Kong, during February 9-12, 2011.

WSDM publishes original, high quality papers and presentations related to search and data mining on the Web and the Social Web, with an emphasis on practical but principled novel models of search, retrieval and data mining, algorithm design and analysis, economics implications, and in-depth experimental analysis of accuracy and performance.

WSDM2011 will have keynotes, invited talks, full paper presentations, posters, tutorials, workshops, social events, etc.  Topics covered include but are not limited to:

Web Search

  * Web Dynamics and Search

  * Multifaceted and task-driven search

  * Multimedia Web search

  * Security and privacy in Web search and mining

  * User interfaces for search interaction

  * Distributed, meta, and peer-to-peer search

  * Vertical portals and search

  * Search quality benchmarking and evaluation

  * Ranking and machine learning for ranking

Web Mining

  * Web measurements, Web evolution, Web models

  * Clustering, classification, and summarization of Web data

  * Opinion mining and sentiment analysis

  * Multimodal data mining

  * Data, entity, event and relationship extraction

  * Sense and entity disambiguation

  * Data integration and data cleaning

  * Discovery-driven Web and social network mining

  * Traffic and log analysis

  * Algorithms and systems for Web-scale search and mining

Social Search and Mining

  * Social network analysis, theories, models, and applications

  * Social media analysis: blogs and friendship networks

  * Social reputation, influence, and trust

  * User profiling and recommendation systems

  * User activity modeling and exploitation

  * Personalized search and ranking

  * Tags, Users, and Search

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