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http://dx.doi.org/10.3745/KIPSTB.2010.17B.2.177

Document Clustering Method using PCA and Fuzzy Association  

Park, Sun (전북대학교 전기전자정보인력양성사업단)
An, Dong-Un (전북대학교 전기전자컴퓨터공학부)
Publication Information
The KIPS Transactions:PartB / v.17B, no.2, 2010 , pp. 177-182 More about this Journal
Abstract
This paper proposes a new document clustering method using PCA and fuzzy association. The proposed method can represent an inherent structure of document clusters better since it select the cluster label and terms of representing cluster by semantic features based on PCA. Also it can improve the quality of document clustering because the clustered documents by using fuzzy association values distinguish well dissimilar documents in clusters. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.
Keywords
Document Clustering; Principal Component Analysis; Semantic Features; Fuzzy Association;
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Times Cited By KSCI : 1  (Citation Analysis)
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