Hierarchical Divisive Clustering with Multi View-Point Based Similarity Measure

  • S. Jayaprada
  • Amarapini Aswani
  • G. Gayathri
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 247)


Clustering is task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. In this paper, we introduce hierarchical divisive clustering with multi view point based similarity measure. The hierarchical clustering is produced by the sequence of repeated bisections. The bisecting incremental k-means with multi view point based similarity measure is used in the clustering. We compare our approach with the existing algorithms on various document collections to verify the advantage of our proposed method.


Hierarchical Clustering Document Clustering Text Mining Similarity Measure 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAnil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia

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