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An Enhancement of Clustering Technique using Support Vector Machine Classifier
Author(s) -
Mehajabi Sayeeda,
Rachana Kamble
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/20526-2863
Subject(s) - computer science , cluster analysis , support vector machine , classifier (uml) , artificial intelligence , machine learning , pattern recognition (psychology) , data mining
Web surfing is very essential task of daily life for any professional person they search information regarding their field. But to get exact required information from ocean internet of data have become complex task. To manage files and information properly document clustering is a good approach. Clustering method divides text information into subgroup on basis of content based similarity. Document clustering reduces searching effort and fulfils human interest information looking for. It groups similar files together to minimize the search time and complexity. This paper gives new clustering method based on hybrid XNOR function to find degree of similarities within any two documents. Resultant similarity used for document clustering by applying SVM classifier for learning network. This paper introduces new method for document clustering by use of similarity matrix calculation and this matrix is passed for training SVM network for upcoming document classification. The results show the effectiveness of proposed work.In this paper, we describe the formatting guidelines for IJCA Journal Submission.

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