Web Search with Personalization and Knowledge

Authors:
George T. Wang;F. Xie;F. Tsunoda;H. Maezawa;Akira K. Onoma
Affiliations:
-;-;-;-;-
Venue:
MSE '02 Proceedings of the Fourth IEEE International Symposium on Multimedia Software Engineering
Year:
2002

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Abstract

Although many search engines provide relevantly good search results to the user, they do not consider personal, domain-specific preferences in their searching or ranking algorithms. In an intranet environment we could collect the background information about the users such as their expertise. If we can accumulate, categorize and personalize web usage information, it can be used to help the user search web pages efficiently and effectively. Data analysis and mining can further facilitate web searching in an intelligent way. This paper describes InternetSearch Advisor (ISA), a personalized, knowledge-driven search system that helps the user find the informative web sites. The ISA supports multi-dimensional data analysis and data mining based on association rules and sequential patterns.