DocumentCode :
2713477
Title :
A Weighted Fuzzy Clustering Algorithm for Data Stream
Author :
Wan, Renxia ; Yan, Xiaoya ; Su, Xiaoke
Author_Institution :
Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai
Volume :
1
fYear :
2008
fDate :
3-4 Aug. 2008
Firstpage :
360
Lastpage :
364
Abstract :
Mining data streams poses great challenges due to the limited memory availability and real time query response requirement. One of the most important mining tasks is clustering. There already lots of clustering algorithms for data stream have been presented. Fuzzy cluster is an important clustering method. However, to the best of our knowledge, all the clustering algorithms are hard clustering methods, fuzzy clustering algorithm is presently not used directly for data streams. Fuzzy c-means (FCM) is a typical fuzzy clustering algorithm. In this paper, we extend FCM and propose a weighted fuzzy algorithm for clustering data stream. Experimental results on both synthetic and real data sets show its superiority over the traditional FCM algorithms.
Keywords :
data mining; fuzzy set theory; pattern clustering; query processing; data stream mining; fuzzy c-means; real time query response; weighted fuzzy clustering algorithm; Clustering algorithms; Clustering methods; Communication system control; Data mining; Educational institutions; Fuzzy control; Image sampling; Machine learning algorithms; Sampling methods; Technology management; Weighted Fuzzy C-Mean; cluster; data stream;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communication, Control, and Management, 2008. CCCM '08. ISECS International Colloquium on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3290-5
Type :
conf
DOI :
10.1109/CCCM.2008.186
Filename :
4609532
Link To Document :
بازگشت