CABOSFV algorithm for high dimensional sparse data clustering

Sen Wu;Xuedong Gao Management School, University of Science and Technology Beijing, Beijing 100083, China

摘 要：<正> An algorithm, Clustering Algorithm Based On Sparse Feature Vector （CABOSFV）, was proposed for the high dimensionalclustering of binary sparse data. This algorithm compresses the data effectively by using a tool ’Sparse Feature Vector’, thus reducesthe data scale enormously, and can get the clustering result with only one data scan. Both theoretical analysis and empirical testsshowed that CABOSFV is of low computational complexity The algorithm finds clusters in high dimensional large datasets effi-ciently and handles noise effectively

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