DocumentCode :
3563603
Title :
Exclusive condition on item partition in fuzzy co-clustering based on K-L information regularization
Author :
Honda, Katsuhiro ; Chi-Hyon Oh ; Notsu, Akira
Author_Institution :
Grad. Sch. of Eng., Osaka Prefecture Univ., Sakai, Japan
fYear :
2014
Firstpage :
1413
Lastpage :
1417
Abstract :
FCCM based on K-L information regularization is an FCM-type co-clustering model, which is a fuzzy counterpart of the probabilistic Multinomial Mixture Models (MMMs). In MMMs and other FCM-type co-clustering models, whose goal is to simultaneously partition objects and items considering their mutual cooccurrence information, memberships of objects are forced to be exclusive in a similar way to FCM while item-memberships only represent the relative typicality in each cluster and are not forced to be exclusive. In this paper, a new co-clustering model is proposed by introducing the penalty for avoiding cluster overlapping in sequential fuzzy cluster extraction, which brings exclusive partition of items.
Keywords :
feature extraction; fuzzy set theory; mixture models; pattern clustering; probability; FCCM; K-L information regularization; MMM; fuzzy cluster extraction; fuzzy coclustering model; item partition; probabilistic multinomial mixture model; Clustering algorithms; Collaboration; Educational institutions; Electronic mail; Fuzzy systems; Linear programming; Probabilistic logic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on
Type :
conf
DOI :
10.1109/SCIS-ISIS.2014.7044636
Filename :
7044636
Link To Document :
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