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Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks

  • Hyoung-rae Kim
  • Philip K. Chan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4198)

Abstract

Personalized web search incorporates an individual user’s interests when deciding relevant results to return. While, most web search engines are usually designed to serve all users, without considering the interests of individual users. We propose a method to (re)rank the results from a search engine using a learned user profile, called a user interest hierarchy (UIH), from web pages that are of interest to the user. The user’s interest in web pages will be determined implicitly, without directly asking the user. Experimental results indicate that our personalized ranking methods, when used with a popular search engine, can yield more potentially interesting web pages for individual users.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hyoung-rae Kim
    • 1
  • Philip K. Chan
    • 2
  1. 1.Web Intelligence LaboratoryGangneung-shi, Gangwon-doSouth Korea
  2. 2.Department of Computer SciencesFlorida Institute of TechnologyMelbourneUSA

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