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DS_CABOSFV clustering algorithm for high dimensional data stream

机译:高维数据流的DS_CABOSFV聚类算法

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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.
机译:数据流群集已成为一个热门研究问题。高维数据流群集是数据流挖掘的难题,因为到达流的大量数据使得大多数传统的算法太低。本文提出了一种基于CabosFv算法的高维数据流聚类算法。我们的经验测试表明,DS_CabosFV具有低计算复杂性和高维数据流聚类的良好效率。

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