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中文摘要：
针对高维聚类算法——相交网格划分算法GCOD存在的缺陷，提出了基于密度度量的相交网格划分聚类算法IGCOD。IGCOD算法对相交网格的尺寸进行控制，重新定义更为合理的密度度量方法，根据密度期望值来合并两个相交的网格。理论分析和实验证明，相对于GCOD算法，基于密度度量的相交网格划分聚类算法IGCOD在性能上有显著的提高。
英文摘要：
To overcome the shortcomings of the GCOD, a high-dimensional clustering algorithm for data mining, the paper proposes an intersected grid clustering algorithm based on density estimation （IGCOD）. The IGCOD algorithm can restrict the size of intersecting grids, redefine the more rational density computing method, and unite the two intersecting grids based on density expectation. The analytical and experimental results show that the IGCOD algorithm proposed in this paper is more efficient than the other existing ones.
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