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Comparative Study of Text Summarization Methods

by Nikita Munot, Sharvari S. Govilkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 102 - Number 12
Year of Publication: 2014
Authors: Nikita Munot, Sharvari S. Govilkar
10.5120/17870-8810

Nikita Munot, Sharvari S. Govilkar . Comparative Study of Text Summarization Methods. International Journal of Computer Applications. 102, 12 ( September 2014), 33-37. DOI=10.5120/17870-8810

@article{ 10.5120/17870-8810,
author = { Nikita Munot, Sharvari S. Govilkar },
title = { Comparative Study of Text Summarization Methods },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 102 },
number = { 12 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume102/number12/17870-8810/ },
doi = { 10.5120/17870-8810 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:22.226740+05:30
%A Nikita Munot
%A Sharvari S. Govilkar
%T Comparative Study of Text Summarization Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 102
%N 12
%P 33-37
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text summarization is one of application of natural language processing and is becoming more popular for information condensation. Text summarization is a process of reducing the size of original document and producing a summary by retaining important information of original document. This paper gives comparative study of various text summarization methods based on different types of application. The paper discusses in detail two main categories of text summarization methods these are extractive and abstractive summarization methods. The paper also presents taxonomy of summarization systems and statistical and linguistic approaches for summarization.

References
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Index Terms

Computer Science
Information Sciences

Keywords

NLP text summarization abstractive summary semantic graph theory linguistic approach statistical approach

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