FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK

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 cooc...

Full description

Bibliographic Details
Main Authors: Katsuhiro Honda, Yurina Suzuki, Seiki Ubukata, Akira Notsu
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Advances in Fuzzy Systems
Online Access:http://dx.doi.org/10.1155/2017/9842127
id doaj-52801ba7cdd9492cba44992b7dfa520e
record_format Article
spelling doaj-52801ba7cdd9492cba44992b7dfa520e2020-11-24T22:34:32ZengHindawi LimitedAdvances in Fuzzy Systems1687-71011687-711X2017-01-01201710.1155/2017/98421279842127FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoKKatsuhiro Honda0Yurina Suzuki1Seiki Ubukata2Akira Notsu3Graduate School of Engineering, Osaka Prefecture University, Sakai, Osaka 599-8531, JapanGraduate School of Engineering, Osaka Prefecture University, Sakai, Osaka 599-8531, JapanGraduate School of Engineering, Osaka Prefecture University, Sakai, Osaka 599-8531, JapanGraduate School of Humanities and Sustainable System Sciences, Osaka Prefecture University, Sakai, Osaka 599-8531, JapanCocluster 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.http://dx.doi.org/10.1155/2017/9842127
collection DOAJ
language English
format Article
sources DOAJ
author Katsuhiro Honda
Yurina Suzuki
Seiki Ubukata
Akira Notsu
spellingShingle Katsuhiro Honda
Yurina Suzuki
Seiki Ubukata
Akira Notsu
FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK
Advances in Fuzzy Systems
author_facet Katsuhiro Honda
Yurina Suzuki
Seiki Ubukata
Akira Notsu
author_sort Katsuhiro Honda
title FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK
title_short FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK
title_full FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK
title_fullStr FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK
title_full_unstemmed FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK
title_sort fcm-type fuzzy coclustering for three-mode cooccurrence data: 3fccm and 3fuzzy codok
publisher Hindawi Limited
series Advances in Fuzzy Systems
issn 1687-7101
1687-711X
publishDate 2017-01-01
description 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.
url http://dx.doi.org/10.1155/2017/9842127
work_keys_str_mv AT katsuhirohonda fcmtypefuzzycoclusteringforthreemodecooccurrencedata3fccmand3fuzzycodok
AT yurinasuzuki fcmtypefuzzycoclusteringforthreemodecooccurrencedata3fccmand3fuzzycodok
AT seikiubukata fcmtypefuzzycoclusteringforthreemodecooccurrencedata3fccmand3fuzzycodok
AT akiranotsu fcmtypefuzzycoclusteringforthreemodecooccurrencedata3fccmand3fuzzycodok
_version_ 1725726965182234624