【摘要】 基于数据流数据的聚类分析算法已成为研究的热点.提出一种基于子空间的高维数据流聚类及演化分析算法CAStream,该算法对数据空间进行网格化,采用近似的方法记录网格单元的统计信息,并将潜在密集网格单元快照以改进的金字塔时间结构进行存储,最后采用深度优先搜索方法进行聚类及其演化分析.CAStream能够有效处理高维数据流,并能发现任意形状分布的聚类.基于真实数据集与仿真数据集的实验表明,算法具有良好的适用性和有效性.更多还原

【Abstract】 Clustering analysis in data stream has become a hot research issue.In this paper,CAStream,a novel algorithm of clustering and evolution analysis over high dimensional data stream is presented,which is based on subspace.CAStream partitions the data space into grids,gets the grid summary statistics using approximate method,then stores snapshots of potential dense girds by improved pyramid time frame,and finally finds the clusters and analyzes the cluster evolution by the depth-first search algorithm.CAStream can deal with high dimensional data stream,and discover the clusters with arbitrary shape.The experimental results on real datasets and synthetic datasets demonstrate the promising availabilities of the approach.更多还原