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Web search personalization with ontological user profiles
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Conference on Information and Knowledge Management archive
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management table of contents
Lisbon, Portugal
SESSION: Web retrieval II (IR) table of contents
Pages 525-534  
Year of Publication: 2007
ISBN:978-1-59593-803-9
Authors
Ahu Sieg  DePaul University, Chicago, IL
Bamshad Mobasher  DePaul University, Chicago, IL
Robin Burke  DePaul University, Chicago, IL
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Every user has a distinct background and a specific goal when searching for information on the Web. The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences. Effective personalization of information access involves two important challenges: accurately identifying the user context and organizing the information in such a way that matches the particular context. 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. A spreading activation algorithm is used to maintain the interest scores based on the user's ongoing behavior. 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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Ahu Sieg: colleagues
Bamshad Mobasher: colleagues
Robin Burke: colleagues