Web Information Systems Engineering, International Conference on (2001)
Dec. 3, 2001 to Dec. 6, 2001
Larry Kerschberg , George Mason University
Wooju Kim , Chonbuk National University
Anthony Scime , SUNY-Brockport
This paper addresses the problem of specifying Web searches and retrieving, filtering, and rating Web pages so as to improve the relevance and quality of hits, based on the user?s search intent and preferences. We present a methodology and architecture for an agent-based system, called WebSifter II, that captures the semantics of a user?s decision-oriented search intent, transforms the semantic query into target queries for existing search engines, and then ranks the resulting page hits according to a user-specified weighted-rating scheme. Users create personalized search taxonomies via our Weighted Semantic-Taxonomy Tree. Consulting a Web taxonomy agent such as Wordnet helps refine the terms in the tree. The concepts represented in the tree are then transformed into a collection of queries processed by existing search engines. Each returned page is rated according to user-specified preferences such as semantic relevance, syntactic relevance, categorical match, page popularity and authority/hub rating.
Meta-search agent, Taxonomy, Personalization, Search engine, Information retrieval
L. Kerschberg, W. Kim and A. Scime, "A Semantic Taxonomy-Based Personalizable Meta-Search Agent," Proceedings of 2nd International Conference on Web Information Systems Engineering(WISE), Kyoto, Japan, 2001, pp. 0041.