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An Online Adaptive Method for Personalization of Search Engines

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3306))

Abstract

A personalized search engine combines a user’s interest into its ranking algorithm and can therefore improve its performance for that particular user. In this paper, we present such a personalized search engine, in which we collect the user’s interest implicitly and dynamically from the user’s profile and measure the similarity at the semantic level. Preliminary experiment results show that our method can achieve a promising improvement after collecting sufficient profile data of a particular user.

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© 2004 Springer-Verlag Berlin Heidelberg

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Huang, G., Wenyin, L. (2004). An Online Adaptive Method for Personalization of Search Engines. In: Zhou, X., Su, S., Papazoglou, M.P., Orlowska, M.E., Jeffery, K. (eds) Web Information Systems – WISE 2004. WISE 2004. Lecture Notes in Computer Science, vol 3306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30480-7_44

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  • DOI: https://doi.org/10.1007/978-3-540-30480-7_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23894-2

  • Online ISBN: 978-3-540-30480-7

  • eBook Packages: Springer Book Archive

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