A Comparative Study on Distance Measuring Approaches for Clustering

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Author(s):
Shraddha Pandit, Suchita Gupta
Published Date:
December 30, 2011
Issue:
Volume 2, Issue 1
Page(s):
29 - 31
DOI:
10.7815/ijorcs.21.2011.011
Views:
4950
Downloads:
531

Keywords:
clustering, distance measure, clustering algorithms
Citation:
Shraddha Pandit, Suchita Gupta, "A Comparative Study on Distance Measuring Approaches for Clustering". International Journal of Research in Computer Science, 2 (1): pp. 29-31, December 2011. doi:10.7815/ijorcs.21.2011.011 Other Formats

Abstract

Clustering plays a vital role in the various areas of research like Data Mining, Image Retrieval, Bio-computing and many a lot. Distance measure plays an important role in clustering data points. Choosing the right distance measure for a given dataset is a biggest challenge. In this paper, we study various distance measures and their effect on different clustering. This paper surveys existing distance measures for clustering and present a comparison between them based on application domain, efficiency, benefits and drawbacks. This comparison helps the researchers to take quick decision about which distance measure to use for clustering. We conclude this work by identifying trends and challenges of research and development towards clustering.

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