DS_CABOSFV clustering algorithm for high dimensional data stream
Jing Pan · 2012
Data stream clustering has become a hot research issue. The high-dimensional data stream clustering is a difficult problem for the data stream mining because the large volumes of data arriving in a stream make most traditional algorithms too inefficient. In this paper, DS_CABOSFV, a high-dimensional data stream clustering algorithm based on CABOSFV algorithm is presented. Our empirical tests show that DS_CABOSFV has low computational complexity and good efficiency for high-dimensional data stream clustering.