Research Article

A SURVEY AUTOMATIC TEXT SUMMARIZATION

Volume: 5 Number: 1 June 30, 2017
EN

A SURVEY AUTOMATIC TEXT SUMMARIZATION

Abstract

Text summarization is compress the source text into a diminished version conserving its information content and overall meaning. Because of the great amount of the information we are provided it and thanks to development of Internet Technologies, text summarization has become an important tool for interpreting text information. Text summarization methods can be classified into extractive and abstractive summarization. An extractive summarization method involves selecting sentences of high rank from the document based on word and sentence features and put them together to generate summary. The importance of the sentences is decided based on statistical and linguistic features of sentences. An abstractive summarization is used to understanding the main concepts in a given document and then expresses those concepts in clear natural language. In this paper, gives comparative study of various text summarization techniques. 

Keywords

References

  1. E. H. Hovy, Automated Text Summarization. The Oxford Handbook of Computational Linguistics, Chapter 32, pages 583-598. Oxford University Press, 2005.
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  6. S.A. Babar, P. D. Patil, “Improving Performance of Text Summarization”, International Conference on Information and Communication Technologies, ICICT, 2014.
  7. Sherry, P. Bhatia, “A Survey to Automatic Summarization Techniques”, International Journal of Engineering Research and General Science Volume 3, Issue 5, September-October, 2015.
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Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Oguzhan Tas This is me

Publication Date

June 30, 2017

Submission Date

May 1, 2017

Acceptance Date

-

Published in Issue

Year 2017 Volume: 5 Number: 1

APA
Tas, O., & Kiyani, F. (2017). A SURVEY AUTOMATIC TEXT SUMMARIZATION. PressAcademia Procedia, 5(1), 205-213. https://doi.org/10.17261/Pressacademia.2017.591
AMA
1.Tas O, Kiyani F. A SURVEY AUTOMATIC TEXT SUMMARIZATION. PAP. 2017;5(1):205-213. doi:10.17261/Pressacademia.2017.591
Chicago
Tas, Oguzhan, and Farzad Kiyani. 2017. “A SURVEY AUTOMATIC TEXT SUMMARIZATION”. PressAcademia Procedia 5 (1): 205-13. https://doi.org/10.17261/Pressacademia.2017.591.
EndNote
Tas O, Kiyani F (June 1, 2017) A SURVEY AUTOMATIC TEXT SUMMARIZATION. PressAcademia Procedia 5 1 205–213.
IEEE
[1]O. Tas and F. Kiyani, “A SURVEY AUTOMATIC TEXT SUMMARIZATION”, PAP, vol. 5, no. 1, pp. 205–213, June 2017, doi: 10.17261/Pressacademia.2017.591.
ISNAD
Tas, Oguzhan - Kiyani, Farzad. “A SURVEY AUTOMATIC TEXT SUMMARIZATION”. PressAcademia Procedia 5/1 (June 1, 2017): 205-213. https://doi.org/10.17261/Pressacademia.2017.591.
JAMA
1.Tas O, Kiyani F. A SURVEY AUTOMATIC TEXT SUMMARIZATION. PAP. 2017;5:205–213.
MLA
Tas, Oguzhan, and Farzad Kiyani. “A SURVEY AUTOMATIC TEXT SUMMARIZATION”. PressAcademia Procedia, vol. 5, no. 1, June 2017, pp. 205-13, doi:10.17261/Pressacademia.2017.591.
Vancouver
1.Oguzhan Tas, Farzad Kiyani. A SURVEY AUTOMATIC TEXT SUMMARIZATION. PAP. 2017 Jun. 1;5(1):205-13. doi:10.17261/Pressacademia.2017.591

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