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

• 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.
• 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.
• 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.
• Violeta, S. ," A Collocation-Driven Approach to Text Summarization". In the TALN 2011 Montpellier, 27 juin – 1erjuillet 2011.
• 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.
• 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
• 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.
• Gülçin, Ö. , Alpaslan, F. and Çiçekli , ?. ," text summarization using latent semantic analysis ". Master thesis, Middle East Technical University, February 2011
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• El-Haj, Mahmoud, Kruschwitz, Chris Fox "University of Essex at the TAC 2011 Multilingual Summarization Pilot".
• 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.
• Zamen,N. , Ghani ,A. "Summarizing Malat Text Documents ",Wrld applied Science Journal 12 Computer Application and Management,30-46,2011,SSN 1818-4952.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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 .
• 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.
• R. He et al. ," Cascaded Regression Analysis Based Temporal Multi-document Summarization ", Informatics 34 (2010) 119–124.