Clustering Data from Heterogeneous Dissimilarities

Authors

  • Prof. Sheetal More  Computer Engineering Department, Sanghavi College of Engineering, Pune University, Nashik, Maharastra, India
  • Prof. Bajirao Shirole  Computer Engineering Department, Sanghavi College of Engineering, Pune University, Nashik, Maharastra, India
  • Roshani Balkrushna Derle  Computer Engineering Department, Sanghavi College of Engineering, Pune University, Nashik, Maharastra, India
  • Rinita Dilip Jadhav  Computer Engineering Department, Sanghavi College of Engineering, Pune University, Nashik, Maharastra, India
  • Shraddha Chandrabhan Jadhav  Computer Engineering Department, Sanghavi College of Engineering, Pune University, Nashik, Maharastra, India
  • Jyoti Yadav Kadale  Computer Engineering Department, Sanghavi College of Engineering, Pune University, Nashik, Maharastra, India

Keywords:

Clustering, Heterogeneous, Centroids, Heuristic, K Mean Algorithm.

Abstract

The clustering model which, to handle the heterogeneity, uses all available dissimilarity matrices and identifies for groups of individuals clustering objects in a similar way. The model is a non-convex problem and difficult to solve exactly, and we thus introduce a Variable Neighborhood Search heuristic to provide solutions efficiently. In our Proposed System we use clustering mechanism to create groups of given heterogeneous datasets, in this system we process heterogeneous data like html and xml as well as numeric data and convert them to single vector by using correlation of values and then this single vector will be clustered by corr-k mean algorithm. output will be number of unlabelled clusters and these clusters will be more precise than what produced by Existing system. In the scope Find centroids and create clusters by automatic clustering method not by iterative method. It can be used to cluster different types of data

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International Journal of Scientific Research in Science and Technology

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Published

2017-04-30

Issue

Volume 3, Issue 3, March-April-2017

Section

Research Articles

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How to Cite

[1]
Prof. Sheetal More, Prof. Bajirao Shirole, Roshani Balkrushna Derle, Rinita Dilip Jadhav, Shraddha Chandrabhan Jadhav, Jyoti Yadav Kadale, " Clustering Data from Heterogeneous Dissimilarities, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 3, pp.396-399, March-April-2017.