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International Workshop on Knowledge Discovery on the Web

WebKDD 2004: Advances in Web Mining and Web Usage Analysis pp 104–115Cite as

Using Hyperlink Features to Personalize Web Search

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3932))

Abstract

Personalized search has gained great popularity to improve search effectiveness in recent years. The objective of personalized search is to provide users with information tailored to their individual contexts. We propose to personalize Web search based on features extracted from hyperlinks, such as anchor terms or URL tokens. Our methodology personalizes PageRank vectors by weighting links based on the match between hyperlinks and user profiles. In particular, here we describe a profile representation using Internet domain features extracted from URLs. Users specify interest profiles as binary vectors where each feature corresponds to a set of one or more DNS tree nodes. Given a profile vector, a weighted PageRank is computed assigning a weight to each URL based on the match between the URL and the profile. We present promising results from an experiment in which users were allowed to select among nine URL features combining the top two levels of the DNS tree, leading to 29 pre-computed PageRank vectors from a Yahoo crawl. Personalized PageRank performed favorably compared to pure similarity based ranking and traditional PageRank.

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Author information

Authors and Affiliations

  1. Computer Science Department, USA

    Mehmet S. Aktas, Mehmet A. Nacar & Filippo Menczer

  2. School of Informatics, Indiana University, Bloomington, IN, 47405, USA

    Filippo Menczer

Authors
  1. Mehmet S. Aktas
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  2. Mehmet A. Nacar
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  3. Filippo Menczer
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Editor information

Editors and Affiliations

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

    Bamshad Mobasher

  2. Speed School of Engineering, Department of Computer Engineering & Computer Science, University of Louisville, KY 40292, Louisville, USA

    Olfa Nasraoui

  3. College of Architecture and Urban Planning, Tongji University, 1239 Siping Road, 200092, Shanghai, P.R. China

    Bing Liu

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

    Brij Masand

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© 2006 Springer-Verlag Berlin Heidelberg

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Aktas, M.S., Nacar, M.A., Menczer, F. (2006). Using Hyperlink Features to Personalize Web Search. In: Mobasher, B., Nasraoui, O., Liu, B., Masand, B. (eds) Advances in Web Mining and Web Usage Analysis. WebKDD 2004. Lecture Notes in Computer Science(), vol 3932. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11899402_7

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  • DOI: https://doi.org/10.1007/11899402_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47127-1

  • Online ISBN: 978-3-540-47128-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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