Research on a Fast Algorithm to Cluster High Dimensional Data

Abstract

Abstract: Clustering is a data mining problem that has received significant attention by the database community. Data set size, dimensionality and sparsity have been identified as aspects that make cluster more difficult. This paper introduces a fast algorithm to cluster large binary data sets where data points have high dimensionality and most of their coordinates are zero. At the end of the paper, it analyzes the algorithm.

摘要： 聚类作为数据挖掘的一个问题已经受到了数据库团体的密切关注。数据集合的大小，数据的维数和数据的稀疏性都是制约聚类的不同方面。文介绍了一种聚类大型二元数据集合的快速算法，在该数据集合中数据点是高维的，并且大多数的坐标值为零。文章最后对算法进行了分析。

关键词: 聚类, 协方差, 稀疏, 数据挖掘

CLC Number:

TP301.6

YAN Xuesong，CAI Zhihua. Research on a Fast Algorithm to Cluster High Dimensional Data[J]. , 2003, 29(01): 140-141.

颜雪松,蔡之华. 一种快速聚类高维数据的算法研究[J]. , 2003, 29(01): 140-141.

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URL: https://www.ecice06.com/EN/Y2003/V29/I01/140

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