Multiple View Point on Cluster Analysis
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2013, Vol 2, Issue 12
Abstract
The clustering methods have to assume some cluster relationship among the data objects that they are applies on. Similarity between a pair of objects can be defines either explicitly or implicitly. In this paper we introduces a novel multi viewpoint based similarity measure and two related clustering methods. The major difference between a traditional dissimilarity/similarity measure and ours is that the former uses only a single viewpoint which is the origin while the latter utilizes many different viewpoints which are objects assumed to not be in the same cluster with the two objects being measures. Using multiple viewpoints more informative assessment of similarity could be achieves. Theoretical analysis and empirical study are conductes to support this claim.
Authors and Affiliations
D. Satya Prasad, Y. Jayababu
Keywords
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