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dc.contributor.advisorChan, Philip K.
dc.contributor.authorHu, Jia
dc.date.accessioned2013-11-14T19:01:02Z
dc.date.available2013-11-14T19:01:02Z
dc.date.issued2008-04-30
dc.identifier.citationHu, J. (2008). Personalized web search by using learned user profiles in re-ranking (CS-2008-02). Melbourne, FL Florida Institute of Technology.en_US
dc.identifier.otherCS-2008-02
dc.identifier.urihttp://hdl.handle.net/11141/173
dc.descriptionA thesis submitted to Florida Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Scienceen_US
dc.description.abstractSearch engines return results mainly based on the submitted query; however, the same query could be in different contexts because individual users have different interests. To improve the relevance of search results, we propose re-ranking results based on a learned user profile. In our previous work we introduced a scoring function for re-ranking search results based on a learned User Interest Hierarchy (UIH). Our results indicate that we can improve relevance at lower ranks, but not at the top 5 ranks. In this thesis, we improve the scoring function by incorporating new term characteristics, image characteristics and pivoted length normalization. Our experimental evaluation shows that the proposed scoring function can improve relevance in each of the top 10 ranks.en_US
dc.language.isoen_USen_US
dc.rightsCopyright held by author.en_US
dc.titlePersonalized web search by using learned user profiles in re-rankingen_US
dc.typeTechnical Reporten_US


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