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Journal of the Korean Society for Library and Information Science

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Vol.37 No.2
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Journal of the Korean Society for Library and Information Science / Journal of the Korean Society for Library and Information Science, (P)1225-598X; (E)2982-6292
2003, v.37 no.2, pp.89-105


& (2003). . Journal of the Korean Society for Library and Information Science, 37(2), 89-105.
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Abstract

In this paper, an effective method for clustering terminologies extracted from text is proposed, in order to develope a search engine to extract relevant information from large web documents. To prevent frequency of the meaningless association rules among general terminologies, only useful association rules among terminologies are produced using database tables which consist of domain-specific terminologies. Such association rules are produced by applying the Apriori algorithm after forming transaction units from groups of association rules in a document. A group of association rules produced from a terminology forms in a cluster.

keywords
데이터마이닝, 연관규칙, 클러스터링, TF?TIDF, Apriori 알고리즘Data Mining, Association Rules, Clustering, TF?TIDF, Apriori Algorithm, 데이터마이닝, 연관규칙, 클러스터링, TF?TIDF, Apriori 알고리즘Data Mining, Association Rules, Clustering, TF?TIDF, Apriori Algorithm

Journal of the Korean Society for Library and Information Science

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