基于混合网格划分的子空间高维数据聚类算法 关键词：高维聚类；子空间聚类；相对熵；网格划分 [gap=970]Key words：high dimensional clustering；subspace clustering；relative entropy；grid partition
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This paper introduces a newly generalized and dynamic structure for the similarity retrieval of high dimensional feature vectors called the recursive clustering index tree.
文章提出了一种新的适用于高维特征矢量相似检索动态聚类索引树结构。
It is hard to cluster high-dimensional data using traditional clustering algorithm because of the sparsity of data.
在高维空间中，由于数据的稀疏性，传统的聚类方法难以有效地聚类高维数据。
The concepts of high attribute dimensional information system are firstly proposed, and a new dynamic clustering method on the basis of sparse feature difference degree is presented.
针对高属性维稀疏数据聚类问题，提出高属性维稀疏信息系统概念，给出一种新的基于稀疏特征差异度的动态抽象聚类方法。
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