期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2011
卷号：8
期号：6
出版社：IJCSI Press
摘要：Personalized web search is able to satisfy individuals information needs by modeling long-term and short-term user interests based on user actions, browsed documents or past queries and incorporate these in the search process. In this paper, we propose a personalized search approach which models the user search preferences in an ontological user profile and semantically compares this model against user current query context to re-rank search results. Our user profile is based on the predefined ontology Open Directory Project (ODP) so that after a user\'s search, relevant web pages are classified into topics in the ontology using semantic and cosine similarity measures. Moreover, interest scores are assigned to topics based on the users ongoing behavior. Our experiments show that re-ranking based on the semantic evidence of the updated user profile efficiently satisfies user information needs with the most relevant results being brought on to the top of the returned results.
关键词：Search Personalization; user profile; ODP; re;rank; semantic similarity
