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An Efficient Text Clustering Approach using Biased Affinity Propagation

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 1
Year of Publication: 2014
Authors:
Isha Sharma
Mahak Motwani
10.5120/16755-6273

Isha Sharma and Mahak Motwani. Article: An Efficient Text Clustering Approach using Biased Affinity Propagation. International Journal of Computer Applications 96(1):1-4, June 2014. Full text available. BibTeX

@article{key:article,
	author = {Isha Sharma and Mahak Motwani},
	title = {Article: An Efficient Text Clustering Approach using Biased Affinity Propagation},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {1},
	pages = {1-4},
	month = {June},
	note = {Full text available}
}

Abstract

Based on an effective clustering algorithm Seeds affinity propagation- in this paper an efficient clustering approach is presented which uses one dimension for the group of the words representing the similar area of interest with that we have also considered the uneven weighting of each dimension depending upon the categorical bias during clustering. After creating the vector the clustering is performed using seeds-affinity clustering technique. Finally to study the performance of the presented algorithm, it is applied to the benchmark data set Reuters-21578 and compared it for F-measure, with k-means algorithm and the original AP (affinity propagation) algorithm the results shows that the presented algorithm outperforms the others by acceptable margin.

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