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

Joint Authors

Ubukata, Seiki
Suzuki, Yurina
Notsu, Akira
Honda, Katsuhiro

Source

Advances in Fuzzy Systems

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

Mathematics

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