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A Detail Survey on Automatic Text Summarization

Rajani S. Sajjan1 , Meera G. Shinde2

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 991-998, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.991998

Online published on Jun 30, 2019

Copyright © Rajani S. Sajjan, Meera G. Shinde . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Rajani S. Sajjan, Meera G. Shinde, “A Detail Survey on Automatic Text Summarization,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.991-998, 2019.

MLA Style Citation: Rajani S. Sajjan, Meera G. Shinde "A Detail Survey on Automatic Text Summarization." International Journal of Computer Sciences and Engineering 7.6 (2019): 991-998.

APA Style Citation: Rajani S. Sajjan, Meera G. Shinde, (2019). A Detail Survey on Automatic Text Summarization. International Journal of Computer Sciences and Engineering, 7(6), 991-998.

BibTex Style Citation:
@article{Sajjan_2019,
author = {Rajani S. Sajjan, Meera G. Shinde},
title = {A Detail Survey on Automatic Text Summarization},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {991-998},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4668},
doi = {https://doi.org/10.26438/ijcse/v7i6.991998}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.991998}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4668
TI - A Detail Survey on Automatic Text Summarization
T2 - International Journal of Computer Sciences and Engineering
AU - Rajani S. Sajjan, Meera G. Shinde
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 991-998
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

the document summarization is becoming essential as lots of information getting generated every day. Instead of going through the entire text document, it is easy to understand the text document fast and easily by a relevant summary. Text summarization is the method of explicitly making a shorter version of one or more text documents. It is a significant method of detecting related material from huge text libraries or from the Internet. It is also essential to extract the information in such a way that the content should be of user’s interest. Text summarization is conducted using two main methods extractive summarization and abstractive summarization. When method select sentences from word document and rank them on basis of their weight to generate summary then that method is called extractive summarization. Abstractive summarization method focuses on main concepts of the document and then expresses those concepts in natural language. Many techniques have been developed for summarization on the basis of these two methods. There are many methods those only work for specific language. Here we discuss various techniques based on abstractive and extractive text summarization methods and shortcomings of different methods

Key-Words / Index Term

Text Summarization, extractive summary, information extraction

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