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Reseach Article

Automatic Text Summarization

by Roshna Chettri, Udit Kr. Chakraborty
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 161 - Number 1
Year of Publication: 2017
Authors: Roshna Chettri, Udit Kr. Chakraborty
10.5120/ijca2017912326

Roshna Chettri, Udit Kr. Chakraborty . Automatic Text Summarization. International Journal of Computer Applications. 161, 1 ( Mar 2017), 5-7. DOI=10.5120/ijca2017912326

@article{ 10.5120/ijca2017912326,
author = { Roshna Chettri, Udit Kr. Chakraborty },
title = { Automatic Text Summarization },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 161 },
number = { 1 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 5-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume161/number1/27110-2017912326/ },
doi = { 10.5120/ijca2017912326 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:06:32.874455+05:30
%A Roshna Chettri
%A Udit Kr. Chakraborty
%T Automatic Text Summarization
%J International Journal of Computer Applications
%@ 0975-8887
%V 161
%N 1
%P 5-7
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Summarization is the art of abstracting key content from one or more information sources [6]. Summarization includes text summarization, image summarization, and video summarization. Text summarization is one of application of natural language processing and is becoming more popular for information condensation [1].Information is accessible in great quantity for every topic on internet assembly the key information in the form of summary would benefit a number of users. Automatic text summarization system generates a summary, i.e. it contains short length text which comprises all the key information of the document. Summary can be generated through extractive as well as abstractive methods.

References
  1. . Johnson, Todd, S. Thede, and A. Vlahov. "PARE: An Automatic Text Summarizer." First Midstates Conference for Undergraduate Research in Computer Science and Mathematics. 2003.
  2. . Madhyastha, Harsha V., N. Balakrishnan, and K. R. Ramakrishnan. "Event information extraction using link grammar." Research Issues in Data Engineering: Multi-lingual Information Management, 2003. RIDE-MLIM 2003. Proceedings. 13th International Workshop on. IEEE, 2003.
  3. . Zang pie-ying et al, “Automatic text summarization based on sentence clustering and extraction” IEEE, 2009.
  4. . Udo Hahn et al. “The Challenges of Automatic Summarization ” IEEE, 2010.
  5. . Sonia Haiduc et al, “On the Use of Automated Text Summarization Techniques for Summarizing Source Code”, 17th Working Conference on Reverse Engineering IEEE,2010.
  6. . Y. Surendranadha Reddy, “An Efficient Approach for Web document summarization by Sentence Ranking”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 7, July 2012.
  7. . Wang, Xuping, et al. "The application of automatic summarization technology in document management." Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on. IEEE, 2013.
  8. . Kamal Sarkar, el at “Automatic Single Document Text Summarization Using Key Concepts in Documents” , J Inf Process Syst, Vol.9, No.4, pp.602-620, December 2013.
  9. . E.Padma Lahari et,“Automatic Text Summarization with Statistical and Linguistic Feature using Successive Thresholds” IEEE(ICACCCT), 2014.
  10. . Luciano Cabral el at,“Automatic Summarization of News Articles for Mobile Devices”. Fourteenth Mexican International Conference on Artificial Intelligence,2015.
Index Terms

Computer Science
Information Sciences

Keywords

Extractive Abstractive natural language processing