FCM-type Cluster Validation in Fuzzy Co-Clustering and Collaborative Filtering Applicability

نویسندگان

  • Katsuhiro Honda
  • Mai Muranishi
  • Akira Notsu
  • Hidetomo Ichihashi
چکیده

FCM-type cluster validation is a technique for searching for the optimal fuzzy partition, in which the number of clusters is evaluated by considering the degree of overlapping of fuzzy memberships, cluster compactness or cluster separation. In this paper, a new approach for FCM-type cluster validation in fuzzy co-clustering is proposed. Because fuzzy co-clustering does not use cluster prototypes, cluster separation is evaluated without using the distances between cluster prototypes. In numerical experiment, the applicability of the new validity measure to collaborative filtering task is studied using a purchase history data.

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تاریخ انتشار 2013