Clustering compatible objects by point neighborhood

Renxia Wan, Lixin Wang, Zijun Hao
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引用次数: 2

Abstract

In some cases, clustering objects into several compatible clusters is more rational than traditional clustering methods do. In this paper, we propose a new compatible clustering algorithm based on CompClustering[8], it adopts point neighborhood technique to replace the iterative mechanism of the latter. Experiments show that the proposed algorithm can get some consistent clustering results, and theory analysis also demonstrates that the proposed algorithm has lower computation consumption than CompClustering does.
通过点邻域聚类兼容对象
在某些情况下,将对象聚到几个兼容的簇中比传统的聚类方法更合理。在本文中,我们提出了一种新的基于CompClustering的兼容聚类算法[8],它采用点邻域技术来取代后者的迭代机制。实验结果表明,该算法能得到一致的聚类结果,理论分析也表明,该算法的计算量比CompClustering更低。
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