FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK
Joint Authors
Ubukata, Seiki
Suzuki, Yurina
Notsu, Akira
Honda, Katsuhiro
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-18
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Honda, Katsuhiro& Suzuki, Yurina& Ubukata, Seiki& Notsu, Akira. 2017. FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK. Advances in Fuzzy Systems،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1121829
Modern Language Association (MLA)
Honda, Katsuhiro…[et al.]. FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK. Advances in Fuzzy Systems No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1121829
American Medical Association (AMA)
Honda, Katsuhiro& Suzuki, Yurina& Ubukata, Seiki& Notsu, Akira. FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK. Advances in Fuzzy Systems. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1121829
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121829