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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 235790, 10 pages
Research Article

A Partitioning Based Algorithm to Fuzzy Tricluster

School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan 454000, China

Received 17 October 2014; Revised 30 December 2014; Accepted 1 January 2015

Academic Editor: Zhan Shu

Copyright © 2015 Yongli Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Fuzzy clustering allows an object to exist in multiple clusters and represents the affiliation of objects to clusters by memberships. It is extended to fuzzy coclustering by assigning both objects and features membership functions. In this paper we propose a new fuzzy triclustering (FTC) algorithm for automatic categorization of three-dimensional data collections. FTC specifies membership function for each dimension and is able to generate fuzzy clusters simultaneously on three dimensions. Thus FTC divides a three-dimensional cube into many little blocks which should be triclusters with strong coherent bonding among its members. The experimental studies on MovieLens demonstrate the strength of FTC in terms of accuracy compared to some recent popular fuzzy clustering and coclustering approaches.