A partitioning based algorithm to fuzzy co-cluster documents and words

Authors:
William-Chandra Tjhi;Lihui Chen
Affiliations:
Division of Information Engineering, School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, Singapore 639798, Republic of Singapore;Division of Information Engineering, School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, Singapore 639798, Republic of Singapore
Venue:
Pattern Recognition Letters
Year:
2006

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Abstract

In this paper, a new algorithm fuzzy co-clustering with Ruspini's condition (FCR) is proposed for co-clustering documents and words. Compared to most existing fuzzy co-clustering algorithms, FCR is able to generate fuzzy word clusters that capture the natural distribution of words, which may be beneficial for information retrieval. We discuss the principle behind the algorithm through some theoretical discussions and illustrations. These, together with experiments on two standard datasets show that FCR can discover the naturally existing document-word co-clusters.