Personalizing web search with folksonomy-based user and document profiles

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Abstract

Web search personalization aims to adapt search results to a user based on his tastes, interests and needs. The way in which such personal preferences are captured, modeled and exploited distinguishes the different personalization strategies. In this paper, we propose to represent a user profile in terms of social tags, manually provided by users in folksonomy systems to describe, categorize and organize items of interest, and investigate a number of novel techniques that exploit the users' social tags to re-rank results obtained with a Web search engine. An evaluation conducted with a dataset from Delicious social bookmarking system shows that our personalization techniques clearly outperform state of the art approaches. © 2010 Springer-Verlag Berlin Heidelberg.

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Vallet, D., Cantador, I., & Jose, J. M. (2010). Personalizing web search with folksonomy-based user and document profiles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5993 LNCS, pp. 420–431). Springer Verlag. https://doi.org/10.1007/978-3-642-12275-0_37

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