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Reseach Article

Text Summarization within the Latent Semantic Analysis Framework: Comparative Study

by Rasha Mohammed Badry, Ahmed Sharaf Eldin, Doaa Saad Elzanfally
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 11
Year of Publication: 2013
Authors: Rasha Mohammed Badry, Ahmed Sharaf Eldin, Doaa Saad Elzanfally
10.5120/14060-2366

Rasha Mohammed Badry, Ahmed Sharaf Eldin, Doaa Saad Elzanfally . Text Summarization within the Latent Semantic Analysis Framework: Comparative Study. International Journal of Computer Applications. 81, 11 ( November 2013), 40-45. DOI=10.5120/14060-2366

@article{ 10.5120/14060-2366,
author = { Rasha Mohammed Badry, Ahmed Sharaf Eldin, Doaa Saad Elzanfally },
title = { Text Summarization within the Latent Semantic Analysis Framework: Comparative Study },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 11 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 40-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number11/14060-2366/ },
doi = { 10.5120/14060-2366 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:55:50.557555+05:30
%A Rasha Mohammed Badry
%A Ahmed Sharaf Eldin
%A Doaa Saad Elzanfally
%T Text Summarization within the Latent Semantic Analysis Framework: Comparative Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 11
%P 40-45
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

It is very difficult for human beings to manually summarize large documents of text. Text summarization solves this problem. Nowadays, Text summarization systems are among the most attractive research areas. Text summarization (TS) is used to provide a shorter version of the original text and keeping the overall meaning. There are various methods that aim to find out well-formed summaries. One of the most commonly used methods is the Latent Semantic Analysis (LSA). In this review, we present a comparative study among almost algorithms based on Latent Semantic Analysis (LSA) approach.

References
  1. Ozsoy. M. G. Text Summarization Using Latent Semantic Analysis, M. sc thesis, Middle East Technical University, 2011.
  2. Ozsoy. M. G. , Cicekli. I. ,and Alpaslan. F. N. 2010. Text Summarization of Turkish Texts using Latent Semantic Analysis Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), pages 869–87.
  3. Hovy, E. H. and Lin, C. Y. 1999. Automated Text Summarization in SUMMARIST. In I. Mani and M. Maybury (eds), Advances in Automated Text Summarization. Cambridge: MIT Press, pp. 81–94.
  4. Gupta,V. , and Lehal. G. S. 2010. A Survey of Text Summarization Extractive Techniques. JOURNAL OF EMERGING TECHNOLOGIES IN WEB INTELLIGENCE, VOL. 2, NO. 3.
  5. Landauer, T. K. , Foltz, P. W. , and Laham, D. 1998. Introduction to Latent Semantic Analysis. Discourse Processes, 25, 259-284.
  6. Hahn. U, and Mani. I. 2000. The challenges of automatic summarization. Computer 33: 29-36.
  7. Lin. C. Y. 2004. ROUGE: a Package for Automatic Evaluation of Summaries. Workshop on Text Summarization Branches Out (WAS 2004). 25-26.
  8. Das. D. , and Martins. A. F. T. 2007. A Survey on Automatic Text Summarization. Literature survey for Language and Statistics II, Carnegie Mellon University.
  9. Gong. Y. , and Liu. X. 2001. Generic text summarization using relevance measure and latent semantic analysis. In Proceedings of ACM SIGIR. New Orleans, USA.
  10. Steinberger, J. and Jezek, K. 2004. Using Latent Semantic Analysis in Text Summarization and Summary Evaluation. Proceedings of ISIM '04, pages 93-100.
  11. Murray, G. , Renals, S. and Carletta, J. 2005. Extractive summarization of meeting recordings. Proceedings of the 9th European Conference on Speech Communication and Technology.
  12. Steinberger, J. and Jezek, K. 2009. Evaluation Measures for Text Summarization. Proceedings of Computing and Informatics, Vol 28, pages 251-275
Index Terms

Computer Science
Information Sciences

Keywords

Text Summarization Latent Semantic Analysis SVD Sentence Extraction.