Research Article
An Efficient Text Clustering Approach using Biased Affinity Propagation
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 96 - Issue 1 |
| Published: June 2014 |
| Authors: Isha Sharma, Mahak Motwani |
10.5120/16755-6273
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Isha Sharma, Mahak Motwani . An Efficient Text Clustering Approach using Biased Affinity Propagation. International Journal of Computer Applications. 96, 1 (June 2014), 1-4. DOI=10.5120/16755-6273
@article{ 10.5120/16755-6273,
author = { Isha Sharma,Mahak Motwani },
title = { An Efficient Text Clustering Approach using Biased Affinity Propagation },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 96 },
number = { 1 },
pages = { 1-4 },
doi = { 10.5120/16755-6273 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Isha Sharma
%A Mahak Motwani
%T An Efficient Text Clustering Approach using Biased Affinity Propagation%T
%J International Journal of Computer Applications
%V 96
%N 1
%P 1-4
%R 10.5120/16755-6273
%I Foundation of Computer Science (FCS), NY, USA
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.
References
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