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Web Usage Data Clustering Using Improved Genetic Fuzzy C-Means Algorithm

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Author(s): Karunesh Gupta | Manish Shrivastava

Journal: International Journal of Advanced Computer Research
ISSN 2249-7277

Volume: 2;
Issue: 2;
Start page: 77;
Date: 2012;
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Keywords: Web Usage Mining | Genetic Algorithm | Fuzzy C-Means

ABSTRACT
Web usage mining involves application of datamining techniques to discover usage patterns fromthe web data. Clustering is one of the importantfunctions in web usage mining. Recent attemptshave adapted the C-means clustering algorithm aswell as genetic algorithms to find sets of clusters .Inthis paper; we have proposed a new framework toimprove the web sessions’ cluster quality from fuzzyc-means clustering using Improved GeneticAlgorithm (GA). Initially a fuzzy c-means algorithmis used to cluster the user sessions. The refinedinitial starting condition allows the iterativealgorithm to converge to a “better” local minimum.And in the second step, we have proposed a new GAbased refinement algorithm to improve the clusterquality. The proposed algorithm is tested with webaccess logs collected from the UCI datasetrepository.
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