DocumentCode :
3698100
Title :
Interval Type-2 fuzzy C-Means approach to collaborative clustering
Author :
Trong Hop Dang; Long Thanh Ngo;Witold Pedrycz
Author_Institution :
Department of Information Systems, Le Quy Don Technical University, 236 Hoang Quoc Viet, Hanoi, Vietnam
fYear :
2015
Firstpage :
1
Lastpage :
7
Abstract :
There have been numerous studies on using the FCM algorithm in clustering and collaboration clustering, especially in data analysis, data mining and pattern recognition. In this study, we present new methods involving interval Type-2 fuzzy sets to realize collaborative clustering. Data in which the clustering results realized at one data site impact clustering carried out at other data sites. Those methods endowed with interval type-2 fuzzy sets help cope with uncertainties present in data. The experiment with weather data sets has shown better results in comparison with the previous approaches.
Keywords :
"Collaboration","Fuzzy sets","Clustering algorithms","Uncertainty","Linear programming","Prototypes","Pattern recognition"
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2015.7337932
Filename :
7337932
Link To Document :
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