Affiliation:
1. Graduate School of Engineering, Osaka Prefecture University, Sakai, Osaka 599-8531, Japan
2. Graduate School of Humanities and Sustainable System Sciences, Osaka Prefecture University, Sakai, Osaka 599-8531, Japan
Abstract
Cocluster structure analysis is a basic technique for revealing intrinsic structural information from cooccurrence data among objects and items, in which coclusters are composed of mutually familiar pairs of objects and items. In many real applications, it is also the case that we have not only cooccurrence information among objects and items but also intrinsic relation among items and other ingredients. For example, in food preference analysis, users’ preferences on foods should be found considering not only user-food cooccurrences but also the implicit relation among users and cooking ingredients. In this paper, two FCM-type fuzzy coclustering models, that is, FCCM and Fuzzy CoDoK, are extended for revealing intrinsic cocluster structures from three-mode cooccurrence data, where the aggregation degree of three elements in each cocluster is maximized through iterative updating of three types of fuzzy memberships for objects, items, and ingredients. The characteristic features of the proposed methods are demonstrated through a numerical experiment.
Funder
Tateisi Science and Technology Foundation
Subject
Computational Mathematics,Control and Optimization,Control and Systems Engineering
Cited by
4 articles.
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