DocumentCode :
2305883
Title :
An improved link analysis based clustering ensemble method
Author :
Wang, Li-juan ; Hao, Zhi-feng
Author_Institution :
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Volume :
1
fYear :
2012
fDate :
15-17 July 2012
Firstpage :
47
Lastpage :
51
Abstract :
This paper proposes an improved link analysis based clustering ensemble method (ILCEM). ILCEM can transform binary data-cluster association matrix into real-valued matrix according to the similarity between clusters in all base clustering. The refined data-cluster association matrix can generate more information to clustering ensemble so as to improve the performance of clustering. Experimental results on three VCI datasets have shown that ILCEM is better than KMC, base clustering method and CSM+GKMC.
Keywords :
matrix algebra; pattern clustering; CSM; GKMC; ILCEM; VCI datasets; binary data-cluster association matrix; link analysis based clustering ensemble method; real-valued matrix; Abstracts; Iris; Robustness; Sonar; K-means clustering; clustering ensemble; link analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location :
Xian
ISSN :
2160-133X
Print_ISBN :
978-1-4673-1484-8
Type :
conf
DOI :
10.1109/ICMLC.2012.6358884
Filename :
6358884
Link To Document :
بازگشت