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Reseach Article

Text Summarization and Classification for Indian Language

by Manasi Chouk, Neelam Phadnis
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 15
Year of Publication: 2021
Authors: Manasi Chouk, Neelam Phadnis
10.5120/ijca2021921471

Manasi Chouk, Neelam Phadnis . Text Summarization and Classification for Indian Language. International Journal of Computer Applications. 183, 15 ( Jul 2021), 1-5. DOI=10.5120/ijca2021921471

@article{ 10.5120/ijca2021921471,
author = { Manasi Chouk, Neelam Phadnis },
title = { Text Summarization and Classification for Indian Language },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2021 },
volume = { 183 },
number = { 15 },
month = { Jul },
year = { 2021 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number15/31999-2021921471/ },
doi = { 10.5120/ijca2021921471 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:16:50.637708+05:30
%A Manasi Chouk
%A Neelam Phadnis
%T Text Summarization and Classification for Indian Language
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 15
%P 1-5
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Over the last few years, there have been significant advances in Text Summarization. Text Summarization can be implemented using two approaches; one is the NLP based approach and another is Deep Learning approach. Text Summarization is a demanding and fascinating field of NLP. It has become important because of the tremendous increase in information and data. Text Summarization is technique of creating a specific and relevant short abstract of text using different ways like books, news articles, research papers, tweets etc. Research is being done to summarize large text documents which are difficult to summarize manually. For English and other foreign languages various automated text summarization systems are available. However very few techniques are available for Indian language such as Marathi. In this paper, two extractive techniques are proposed to summarize large Marathi texts. This paper also performs classification on Marathi text using Marathi headlines dataset.

References
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Index Terms

Computer Science
Information Sciences

Keywords

NLP Extractive technique TF-IDF Text Rank Marathi Language