Title :
Extending fuzzy c-means to clustering data streams
Author :
Mostafavi, Sara ; Amiri, Ali
Author_Institution :
Dept. of Comput. Eng., Univ. of Zanjan, Zanjan, Iran
Abstract :
A data stream is an ordered and continuous sequence of examples that can be examined only once. Data stream mining introduces new challenges compared to traditional mining algorithms. Fuzzy c-means (FCM) is a method of clustering in which a data point can assign to more than one cluster at the same time. In this paper we extend FCM algorithm to clustering data streams. Our performance experiments over KDD-CUP´99 data set show the efficiency of the algorithm.
Keywords :
data analysis; data mining; fuzzy set theory; media streaming; FCM algorithm; KDD-CUP´99 data set; data mining; data point; data stream clustering; fuzzy c-means; Fuzzy c-means; data stream; fuzzy clustering;
Conference_Titel :
Electrical Engineering (ICEE), 2012 20th Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4673-1149-6
DOI :
10.1109/IranianCEE.2012.6292449
