DocumentCode
3430587
Title
A new K-means algorithm for community structures detection based on fuzzy clustering
Author
Liu, Qun ; Peng, Zhiming ; Gao, Yi ; Liu, Qian
Author_Institution
Chongqing key laboratory of computational intelligence, Chongqing University of Posts and Telecommunications, China
fYear
2012
fDate
11-13 Aug. 2012
Firstpage
1
Lastpage
5
Abstract
Finding community structures from networks is one of the most popular research areas in recent years. Because of the shortcoming of FCM, for example, its results depend on the initial center node and need to specify the community number, based on the fuzzy theory, an improved FCM algorithm(NKFCM) is proposed, which can get the number of communities and the community centers automatically. NKFCM is used to find the communities of network. The experiments in real networks show that this method can get better results.
Keywords
Biology; Biomedical optical imaging; Communities; Image edge detection; Laboratories; Community structure; Fuzzy C-Means clustering; K-means algorithm; Social network;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2012 IEEE International Conference on
Conference_Location
Hangzhou, China
Print_ISBN
978-1-4673-2310-9
Type
conf
DOI
10.1109/GrC.2012.6468579
Filename
6468579
Link To Document