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Structure Identification-Based Clustering According to Density Consistency

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  • Chunzhong Li
  • Zongben Xu

Abstract

Structure of data set is of critical importance in identifying clusters, especially the density difference feature. In this paper, we present a clustering algorithm based on density consistency, which is a filtering process to identify same structure feature and classify them into same cluster. This method is not restricted by the shapes and high dimension data set, and meanwhile it is robust to noises and outliers. Extensive experiments on synthetic and real world data sets validate the proposed the new clustering algorithm.

Suggested Citation

  • Chunzhong Li & Zongben Xu, 2011. "Structure Identification-Based Clustering According to Density Consistency," Mathematical Problems in Engineering, Hindawi, vol. 2011, pages 1-14, October.
    • Handle: RePEc:hin:jnlmpe:890901
    DOI: 10.1155/2011/890901
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