CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Text Summarization using Centrality Concept

by Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 79 - Number 1
Year of Publication: 2013
Authors: Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram
10.5120/13703-1450

Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram . Text Summarization using Centrality Concept. International Journal of Computer Applications. 79, 1 ( October 2013), 5-12. DOI=10.5120/13703-1450

@article{ 10.5120/13703-1450,
author = { Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram },
title = { Text Summarization using Centrality Concept },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 79 },
number = { 1 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 5-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume79/number1/13703-1450/ },
doi = { 10.5120/13703-1450 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:53.184523+05:30
%A Ghaleb Algaphari
%A Fadl M. Ba-alwi
%A Aimen Moharram
%T Text Summarization using Centrality Concept
%J International Journal of Computer Applications
%@ 0975-8887
%V 79
%N 1
%P 5-12
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The amount of textual information available on the web is estimated by terra bytes. Therefore constructing a software program to summarize web pages or electronic documents would be a useful technique. Such technique would speed up of reading, information accessing and decision making process. This paper investigates a graph based centrality algorithm on Arabic text summarization problem (ATS). The graph based algorithm depends on extracting the most important sentences in a documents or a set of documents (cluster). The algorithm starts computing the similarity between two sentences and evaluating the centrality of each sentence in a cluster based on centrality graph. Then the algorithm extracts the most important sentences in the cluster to include them in a summary. The algorithm is implemented and evaluated by human participants and by an automatic metrics. Arabic NEWSWIRE-a corpus is used as a data set in the algorithm evaluation. The result was very promising.

References
  1. Haboush, A. ,Al-zoubi, M. ,Momani, A. and Tarazi, M. " Arabic Text Summarization Model Using Clustering Techniques". In the World of Computer Science and Information Technology Journal (WCSIT), Vol. 2, No. 3, 62 – 67, 2012.
  2. Thakkar, K. and Shrawankar, U. "Test Model for Text Categorization and Text Summarization ". In the International Journal on Computer Science and Engineering(IJCSE) ,vol. 3. No. 4 Apr 2011, India.
  3. Vijayapal Reddy, P. , Vishnu vardhan,B. and Govardhan,A. ," Analysis of BMW Model for Title Word Selection on Indic Script ". In the International Journal of Computer Applications (0975 – 8887) Volume 18– No. 8, March 2011.
  4. Violeta, S. ," A Collocation-Driven Approach to Text Summarization". In the TALN 2011 Montpellier, 27 juin – 1erjuillet 2011.
  5. Greenbacker1, C. F. , McCoy1, K. F. , Carberry1, S. and McDonald. D. , "Semantic Modeling of Multimodal Documents for Abstractive Summarization ". In the Proceedings of the Workshop on Automatic Text Summarization Collocated with Canadian Conference on Artificial Intelligence, 2011, Canada.
  6. Nagwani, N. and Verma,S. ," A Frequent Term and Semantic Similarity based Single Document Text Summarization Algorithm ". In the International Journal of Computer Applications (0975 – 8887) Volume 17– No. 2, March 2011
  7. Yasin,H. , Yasin,M, Yasin,F. ," Automated Multiple Related Documents Summarization via Jaccard's Coefficient ". In the International Journal of Computer Applications (0975 – 8887) ,Volume 13– No. 3, January 2011, Pakistan.
  8. Gülçin, Ö. , Alpaslan, F. and Çiçekli , ?. ," text summarization using latent semantic analysis ". Master thesis, Middle East Technical University, February 2011
  9. Zamin, N. and Ghani,A. ," Summarizing Malay Text Documents". In the World Applied Sciences Journal12 (Special Issue on Computer Application & knowledge management):39-46, 2011, Malaysia.
  10. Saggion , H. , " Using SUMMA for Language Independent Summarization at TAC 2011 ". In the proceeding of the TAC 2011 Workshop November, 2011, National Institute of Standards and Technology Gaithersburg, Maryland USA.
  11. Delort,J. and Alfonseca,E. ," Description of the Google update summarizer at TAC-2011 " . In the proceeding of the TAC 2011 Workshop November, 2011, National Institute of Standards and Technology Gaithersburg, Maryland USA.
  12. Kogilavani, A. and Balasubramani, P. "Clustering and feature specific sentence extraction based summarization of multiple documents ". International journal of computer science & information Technology (IJCSIT) Vol. 2, No. 4, August 2010.
  13. Saggion, H. , Torres-Moreno,J. , da Cunha,I. , SanJuan,E. and Vel ´ azquez-Morales,P. " Multilingual Summarization Evaluation without Human Models " . In the Coling 2010: Poster Volume, pages 1059–1067,Beijing, August 2010.
  14. Erkan, G. and Radev, R. , " LexRank : Graph-based Lexical Centrality as Salience in Text Summarization". In the Journal of Artificial Intelligence Research 22 (2004) 457-479.
  15. El-Haj, Mahmoud, Kruschwitz, Chris Fox "University of Essex at the TAC 2011 Multilingual Summarization Pilot".
  16. Haboush,A. , Momani, A. , Al-Zoubi,M. , Tarazi,M. " Arabic Text Summarization Model Using Clustering Techniques", World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 2, No. 3, 62 – 67, 2012.
  17. Zamen,N. , Ghani ,A. "Summarizing Malat Text Documents ",Wrld applied Science Journal 12 Computer Application and Management,30-46,2011,SSN 1818-4952.
  18. A. Kogilavani1 and Dr. P. Balasubramani2," Clustering and feature specific sentence extraction based Summarization of multiple documents ", International journal of computer science & information Technology (IJCSIT) Vol. 2, No. 4, August 2010 ,DOI : 10. 5121/ijcsit. 2010. 2409 99.
  19. Perumal ,P. and Nedunchezhian ,R. " Performance Evaluation of Three Model-Based Documents Clustering Algorithms "European Journal of Scientific Research ISSN 1450-216X Vol. 52 No. 4 (2011), pp. 618-628 © Euro Journals Publishing, Inc. 2011. http://www. eurojournals. com/ejsr. htm.
  20. Thakkar K. and Shrawankar U. ," Test Model for Text Categorization and Text Summarization ", International Journal on Computer Science and Engineering (IJCSE), ISSN: 0975-3397 Vol. 3 No. 4 Apr 2011.
  21. Yasin, H. , Yasin, M. and Yasin, F. ," Automated Multiple Related Documents Summarization via Jaccard's Coefficient "International Journal of Computer Applications (0975 – 8887)Volume 13– No. 3, January 2011.
  22. Nagwani, N. and Verma,S. "A Frequent Term and Semantic Similarity based Single Document Text Summarization Algorithm ",International Journal of Computer Applications (0975 – 8887) Volume 17– No. 2, March 2011.
  23. Haboush,A. , Momani,A. , Al-Zoubi,M. , Tarazi,M. "Arabic Text Summerization Model Using Clustering Techniques ",World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 2, No. 3, 62 – 67, 2012 .
  24. Reddy, P. , Mahendra,R. , vardhan,B. , and Govardhan,A. ," Analysis of BMW Model for Title Word Selection on Indic Script ",International Journal of Computer Applications (0975 – 8887) Volume 18– No. 8, March 2011.
  25. R. He et al. ," Cascaded Regression Analysis Based Temporal Multi-document Summarization ", Informatics 34 (2010) 119–124.
Index Terms

Computer Science
Information Sciences

Keywords

Text Summarization Text Mining and Centrality Concept

Powered by PhDFocusTM