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Using Data Fusion for a Context Aware Document Clustering

by P. Venkateshkumar, A. Subramani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 6
Year of Publication: 2013
Authors: P. Venkateshkumar, A. Subramani
10.5120/12497-7430

P. Venkateshkumar, A. Subramani . Using Data Fusion for a Context Aware Document Clustering. International Journal of Computer Applications. 72, 6 ( June 2013), 17-20. DOI=10.5120/12497-7430

@article{ 10.5120/12497-7430,
author = { P. Venkateshkumar, A. Subramani },
title = { Using Data Fusion for a Context Aware Document Clustering },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 6 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 17-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number6/12497-7430/ },
doi = { 10.5120/12497-7430 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:37:12.680084+05:30
%A P. Venkateshkumar
%A A. Subramani
%T Using Data Fusion for a Context Aware Document Clustering
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 6
%P 17-20
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The large volume of unstructured text data available at various sources such as digital libraries, news, internet, has given arise a need to organize the information as per the user's requirement. Search for relevant information is efficient when context of the selected word in the document is considered. Document Clustering aims to discover natural groupings, and present an overview of classes (topics) in a document collection. Thus, documents with similar contents are related to the same query. In this paper, a new method for clustering documents is proposed. In the proposed method, the term frequency of the document collection is computed and contexts based terms are fused. Agglomerative clustering and Bisecting K-Means are used to cluster the extracted features.

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Index Terms

Computer Science
Information Sciences

Keywords

Document clustering term frequency Bisecting K-means Agglomerative clustering Reuters dataset

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