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Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks

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Book cover Advances in Web Mining and Web Usage Analysis (WebKDD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4198))

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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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Author information

Authors and Affiliations

  1. Web Intelligence Laboratory, Hongje-dong, 158 bungi, Prugio 101dong 104ho, Gangneung-shi, Gangwon-do, 210-948, South Korea

    Hyoung-rae Kim

  2. Department of Computer Sciences, Florida Institute of Technology, Melbourne, FL, 32901, USA

    Philip K. Chan

Authors
  1. Hyoung-rae Kim
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  2. Philip K. Chan
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Editor information

Editors and Affiliations

  1. Knowledge Discovery & Web Mining Lab, University of Louisville, 40292, Louisville, KY, USA

    Olfa Nasraoui

  2. University of Alberta, Canada

    Osmar Zaïane

  3. Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

    Myra Spiliopoulou

  4. Center for Web Intelligence School of Computing, DePaul University, Chicago, Illinois, USA

    Bamshad Mobasher

  5. Data Miners Inc., 77 North Washington Street, 02114, Boston, MA, USA

    Brij Masand

  6. University of Illinois, Chicago, IL, USA

    Philip S. Yu

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© 2006 Springer-Verlag Berlin Heidelberg

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Kim, Hr., Chan, P.K. (2006). Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks. In: Nasraoui, O., Zaïane, O., Spiliopoulou, M., Mobasher, B., Masand, B., Yu, P.S. (eds) Advances in Web Mining and Web Usage Analysis. WebKDD 2005. Lecture Notes in Computer Science(), vol 4198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11891321_9

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  • DOI: https://doi.org/10.1007/11891321_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46346-7

  • Online ISBN: 978-3-540-46348-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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