Preference Modeling and Mining for Personalization

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Author(s): Seung-won Hwang (Pohang University of Science and Technology (POSTECH), Korea)
Copyright: 2009
Pages: 5
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch240

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Abstract

As near-infinite amount of data are becoming accessible on the Web, it becomes more important to support intelligent personalized retrieval mechanisms, to help users identify the results of a manageable size satisfying user-specific needs. Example case studies include major search engines, such as Google and Yahoo, recently released personalized search, which adapts the ranking to the user-specific search context. Similarly, e-commerce sites, such as Amazon, are providing personalized product recommendation based on the purchase history and user browsing behaviors. To achieve this goal, it is important to model user preference and mine user preferences from user behaviors (e.g., click history) for personalization. In this article, we discuss recent efforts to extend mining research to preference and identify goals for the future works.

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