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http://dx.doi.org/10.3745/KIPSTB.2006.13B.5.533

Personalized Search Service in Semantic Web  

Kim, Je-Min (숭실대학교 대학원 컴퓨터학과)
Park, Young-Tack (숭실대학교 컴퓨터학과)
Publication Information
The KIPS Transactions:PartB / v.13B, no.5, 2006 , pp. 533-540 More about this Journal
Abstract
The semantic web environment promise semantic search of heterogeneous data from distributed web page. Semantic search would resuit in an overwhelming number of results for users is increased, therefore elevating the need for appropriate personalized ranking schemes. Culture Finder helps semantic web agents obtain personalized culture information. It extracts meta data for each web page(culture news, culture performance, culture exhibition), perform semantic search and compute result ranking point to base user profile. In order to work efficient, Culture Finder uses five major technique: Machine learning technique for generating user profile from user search behavior and meta data repository, an efficient semantic search system for semantic web agent, query analysis for representing query and query result, personalized ranking method to provide suitable search result to user, upper ontology for generating meta data. In this paper, we also present the structure used in the Culture Finder to support personalized search service.
Keywords
Semantic Web; Ontology; Meta-data; Personalized Information Search;
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