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Reseach Article

Automatic Document Collection

by Shashikant, Mukesh Rawat
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 25
Year of Publication: 2013
Authors: Shashikant, Mukesh Rawat
10.5120/12221-8137

Shashikant, Mukesh Rawat . Automatic Document Collection. International Journal of Computer Applications. 70, 25 ( May 2013), 9-12. DOI=10.5120/12221-8137

@article{ 10.5120/12221-8137,
author = { Shashikant, Mukesh Rawat },
title = { Automatic Document Collection },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 25 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number25/12221-8137/ },
doi = { 10.5120/12221-8137 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:33:47.331441+05:30
%A Shashikant
%A Mukesh Rawat
%T Automatic Document Collection
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 25
%P 9-12
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Now a day's classification of document is an important area for research, as large amount of electronic documents are available in form of unstructured, semi structured and structured information. Document classification will be applicable for World Wide Web, electronic book sites, online forums, electronic mails, online blogs, digital libraries and online government repositories. So it is necessary to organize the information and proper categorization and knowledge discovery is also important. This paper focused on the existing literature and explored the techniques for automatic documents classification i. e. documents representation, knowledge extraction and classification. In this paper author propose an algorithm and architecture for automatic document collection.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Text mining Web mining Automatic document classification