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강보영(Bo-Yeong Kang),김대원(KAIST)(Dae-Won Kim(KAIST)),구상옥(Sang-Ok Gu),이상조(Sang-Jo Lee) 한국정보과학회 2002 한국정보과학회 학술발표논문집 Vol.29 No.1B
If there is an Information Retrieval system which comprehends the semantic content of documents and knows the preference of users, the system can search the information better on the Internet, or improve the IR performance. Therefore we propose the IR model which combines semantic based indexing and fuzzy relevance model. In addition to the statistical approach, we chose the semantic approach in indexing, lexical chains, because we assume it would improve the performance of the index term extraction. Furthermore, we combined the semantic based indexing with the fuzzy model, which finds out the exact relevance of the user preference and index terms. The proposed system works as follows: First, the presented system indexes documents by the efficient index term extraction method using lexical chains. And then, if a user tends to retrieve the information from the indexed document collection, the extended IR model calculates and ranks the relevance of user query, user preference and index terms by some metrics. When we experimented each module, semantic based indexing and extended fuzzy model, it gave noticeable results. The combination of these modules is expected to improve the information retrieval performance.
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