A hybrid approach using genetic algorithm and the differential evolution heuristic for enhanced initialization of the k-means algorithm with applications in text clustering-Reference-Cited by-同舟云学术

A hybrid approach using genetic algorithm and the differential evolution heuristic for enhanced initialization of the k-means algorithm with applications in text clustering

Published:2018-06-07 Issue:15 Volume:23 Page:6361-6378
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Mustafi D.^ORCID,Sahoo G.

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-018-3289-4.pdf

Reference57 articles.

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3. Al-Shboul B, Myaeng SH (2006) Initializing k-means using genetic algorithms. PhD thesis, University of Jordan

4. Alshamiri AK, Singh A, Surampudi BR (2016) Artificial bee colony algorithm for clustering: an extreme learning approach. Soft Comput 20(8):3163–3176

5. Arellano-Verdejo J, Alba E, Godoy-Calderon S (2016) Efficiently finding the optimum number of clusters in a dataset with a new hybrid differential evolution algorithm: DELA. Soft Comput 20(3):895–905

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