Indexed by：
Abstract：
Data stream clustering is an importance issue in data stream mining. In most of the existing algorithms, only the continuous features are used for clustering. In this paper, we introduce an algorithm HDenStream for clustering data stream with heterogeneous features. The HDenstream is also a density-based algorithm, so it is capable enough to cluster arbitrary shapes and handle outliers. Theoretic analysis and experimental results show that HDenStream is effective and efficient. ©2009 IEEE.
Keyword：
Reprint 's Address：
Email：
Source ：
Year： 2009
Volume： 4
Page： 275-277
Language： English
Cited Count：
SCOPUS Cited Count： 20
ESI Highly Cited Papers on the List： 0 Unfold All
WanFang Cited Count：
Chinese Cited Count：
30 Days PV： 1
Affiliated Colleges：
