摘要
An algorithm, Clustering Algorithm Based On Sparse Feature Vector (CABOSFV), was proposed for the high dimensional clustering of binary sparse data. This algorithm compresses the data effectively by using a tool 'Sparse Feature Vector', thus reduces the data scale enormously, and can get the clustering result with only one data scan. Both theoretical analysis and empirical tests showed that CABOSFV is of low computational complexity. The algorithm finds clusters in high dimensional large datasets efficiently and handles noise effectively.
An algorithm, Clustering Algorithm Based On Sparse Feature Vector (CABOSFV),was proposed for the high dimensional clustering of binary sparse data. This algorithm compressesthe data effectively by using a tool 'Sparse Feature Vector', thus reduces the data scaleenormously, and can get the clustering result with only one data scan. Both theoretical analysis andempirical tests showed that CABOSFV is of low computational complexity. The algorithm findsclusters in high dimensional large datasets efficiently and handles noise effectively.
