Proceedings of the 11th international conference on World Wide Web
Persona: A Contextualized and Personalized Web Search
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 3 - Volume 3
Personalized Web Search For Improving Retrieval Effectiveness
IEEE Transactions on Knowledge and Data Engineering
Ontology-based personalized search and browsing
Web Intelligence and Agent Systems
Ontological User Profiles for Representing Context in Web Search
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Using hyperlink features to personalize web search
WebKDD'04 Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Ontological User Profiles for Representing Context in Web Search
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Personalized cluster-based semantically enriched web search for e-learning
Proceedings of the 2nd international workshop on Ontologies and information systems for the semantic web
Ontology-based web service to recommend spare time activities
Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Personal ontologies: Generation of user profiles based on the YAGO ontology
Information Processing and Management: an International Journal
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The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences. We present an approach to personalized search that involves building models of user context as ontological profiles by assigning implicitly derived interest scores to existing concepts in a domain ontology. Our experiments show that re-ranking the search results based on the interest scores and the semantic evidence in an ontological user profile is effective in presenting the most relevant results to the user.