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
- E. H. Hovy, Automated Text Summarization. The Oxford Handbook of Computational Linguistics, Chapter 32, pages 583-598. Oxford University Press, 2005.
- I. Mani, D. House, G. Klein, The TIPSTER SUMMAC Text Summarization Evaluation. In Proceedings of EACL, 1999.
- H. P. Luhn, "The automatic creation of literature abstracts”, IBM Journal of Research and Development, vol. 2, pp. 159-165, 1958.
- U. Hahn, & I. Mani, “The challenges of automatic summarization” IEEE-Computer, 33(11), 29–36, 2000.
- V. Gupta, G.S. Lehal, “A survey of Text Summarization Extractive Techniques”, Journal of Emerging Technologies in Web Intelligence, Vol. 2, No.3, August 2010.
- S.A. Babar, P. D. Patil, “Improving Performance of Text Summarization”, International Conference on Information and Communication Technologies, ICICT, 2014.
- Sherry, P. Bhatia, “A Survey to Automatic Summarization Techniques”, International Journal of Engineering Research and General Science Volume 3, Issue 5, September-October, 2015.
- S. Karmakar, T. Lad, H. Chothani, A Review Paper on Extractive Techniques of Text Summarization, International Research Journal of Computer Science (IRJCS) Issue 1, Volume 2, 2015.
Details
Primary Language
English
Subjects
-
Journal Section
Research Article
Publication Date
June 30, 2017
Submission Date
May 1, 2017
Acceptance Date
-
Published in Issue
Year 2017 Volume: 5 Number: 1