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Document Clustering: A Detailed Review

by Neepa Shah, Sunita Mahajan
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 5
Year of Publication: 2012
Authors: Neepa Shah, Sunita Mahajan
10.5120/ijais12-450691

Neepa Shah, Sunita Mahajan . Document Clustering: A Detailed Review. International Journal of Applied Information Systems. 4, 5 ( October 2012), 30-38. DOI=10.5120/ijais12-450691

@article{ 10.5120/ijais12-450691,
author = { Neepa Shah, Sunita Mahajan },
title = { Document Clustering: A Detailed Review },
journal = { International Journal of Applied Information Systems },
issue_date = { October 2012 },
volume = { 4 },
number = { 5 },
month = { October },
year = { 2012 },
issn = { 2249-0868 },
pages = { 30-38 },
numpages = {9},
url = { https://www.ijais.org/archives/volume4/number5/300-0691/ },
doi = { 10.5120/ijais12-450691 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:47:26.237113+05:30
%A Neepa Shah
%A Sunita Mahajan
%T Document Clustering: A Detailed Review
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 4
%N 5
%P 30-38
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Document clustering is automatic organization of documents into clusters so that documents within a cluster have high similarity in comparison to documents in other clusters. It has been studied intensively becauseof its wide applicability in various areas such as web mining,search engines, and information retrieval. It is measuring similarity between documents and grouping similardocuments together. It providesefficient representation and visualization of thedocuments; thus helps in easy navigation also. In this paper, we have given overview of various document clustering methodsstudied and researched since last few years,starting from basic traditional methods to fuzzy based, genetic, co-clustering, heuristic oriented etc. Also, the document clustering procedure with feature selection process, applications, challenges in document clustering, similarity measures and evaluation of document clustering algorithm is explained.

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Index Terms

Computer Science
Information Sciences

Keywords

Document clustering document clustering applications document clustering procedure similarity measures for document clustering evaluation of document clustering algorithm challenges in document clustering

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