Modeling Web Searcher Behavior and Interactions

author: Eugene Agichtein, Department of Mathematics and Computer Science, Emory University
published: April 15, 2010,   recorded: September 2009,   views: 3891

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Hundreds of millions of users search the web daily, clicking on the results, submitting and refining queries and otherwise interacting with the search engines. The vast amount of information generated as a by-product of these interactions can be mined to dramatically improve the effectiveness of web search, and information access in general. This course will survey the research in modeling user behavior in web search, and how this information can improve web search effectiveness. The emphasis will be on learning and analyzing the appropriate data mining and machine learning techniques for the user behavior and interaction data, and on the integration of the behavioral models into the search engine operation.

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