Relative Reference Measure for Hierarchical Document Clustering
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 12
Abstract
Clustering is a foremost concept in data mining. Clustering usually require a measure that needs to be computed among the clustering objects this measure could be either a similarity or a dissimilarity measure, here a multiple relative reference based similarity measure is used which could give more informative assessment of the similarity moreover this measure is derived from the traditional cosine similarity measure. In order to evaluate the performance of proposed measure an incremental clustering algorithm- Master only algorithm is used initially with cosine similarity and then with Relative Reference similarity measures for document clustering. As an extended application of Relative Reference measure to generate hierarchical clusters we used Master-Slave algorithm. The results of clustering are evaluated by using a cluster validity index-Davies Bouldin index.
Authors and Affiliations
D. Satya Prasad, T. Nirosh Kumar
Keywords
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