An Approach to Clustering of Text Documents Using Graph Mining Techniques

B. Rao, B. K. Mishra
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引用次数: 32

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. KeywoRDS Bi-partite Graph Clustering, Self-loop, Sub-graph, Weighted Un-Oriented Incidence Matrix
一种基于图挖掘技术的文本文档聚类方法
本文介绍了一种基于词集的文本文档聚类的新方法。所建议的方法将那些从一组给定文本文档中成功搜索到给定单词集的文本文档聚类(分组)。文档-词关系可以表示为一个双部图。所有文本文档的聚类都表示为子图。此外,本文提出了一种针对给定词集的文本文档聚类算法。它是一个自动化系统,对文本文档的聚类需要最少的人工交互。该算法已用c++编程语言实现,取得了满意的效果。关键词:二分图聚类,自环,子图,加权无向关联矩阵
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