Welcome to the InfoSci Platform
Reference Hub8
An Approach to Clustering of Text Documents Using Graph Mining Techniques

An Approach to Clustering of Text Documents Using Graph Mining Techniques

Bapuji Rao, Brojo Kishore Mishra
Copyright: © 2017 |Volume: 4 |Issue: 1 |Pages: 18
ISSN: 2334-4598|EISSN: 2334-4601|EISBN13: 9781522515715|DOI: 10.4018/IJRSDA.2017010103
Cite Article Cite Article

MLA

Rao, Bapuji, and Brojo Kishore Mishra. "An Approach to Clustering of Text Documents Using Graph Mining Techniques." IJRSDA vol.4, no.1 2017: pp.38-55. http://doi.org/10.4018/IJRSDA.2017010103

APA

Rao, B. & Mishra, B. K. (2017). An Approach to Clustering of Text Documents Using Graph Mining Techniques. International Journal of Rough Sets and Data Analysis (IJRSDA), 4(1), 38-55. http://doi.org/10.4018/IJRSDA.2017010103

Chicago

Rao, Bapuji, and Brojo Kishore Mishra. "An Approach to Clustering of Text Documents Using Graph Mining Techniques," International Journal of Rough Sets and Data Analysis (IJRSDA) 4, no.1: 38-55. http://doi.org/10.4018/IJRSDA.2017010103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This paper introduces a new approach of clustering of text documents based on a set of words using graph mining techniques. The proposed approach clusters (groups) those text documents having searched successfully for the given set of words from a set of given text documents. The document-word relation can be represented as a bi-partite graph. All the clustering of text documents is represented as sub-graphs. Further, the paper proposes an algorithm for clustering of text documents for a given set of words. It is an automated system and requires minimal human interaction for the clustering of text documents. The algorithm has been implemented using C++ programming language and observed satisfactory results.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.