期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：4
出版社：S&S Publications
摘要：Recently many researchers have focused on mining data streams and they proposed many techniques and algorithms for data stream s . They are data stream classification, data stream clustering , and data stream frequent pattern items and so on. Data stream clustering techniques are highly helpful to cluster the similar data items in data streams and also to detect the outliers, so they are called cluster based outlier detection. The main objecti ve of this research work is to perform the clustering process and detecting the outliers in data streams. In this research work, two partitioning clustering algorithms namel y CLARANS and E - CLARANS (Enhanced Clarans) are used for clustering and detecting the outliers in data streams. Two performance factors such as clustering accuracy and outlier detectio n accuracy are used for observation. By examining the experimental results, it is observed that the proposed E - CLARANS clustering algorithm performance is more accura te than the existing algorithm CLARANS.
关键词：Data stream; Data stream clustering; Outlier detection; CLARANS; E ; CLARANS
