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Reseach Article

A Hybrid Intelligent System for Abstractive Summarization

by Dania Sagheer, Fadel Sukkar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 168 - Number 9
Year of Publication: 2017
Authors: Dania Sagheer, Fadel Sukkar
10.5120/ijca2017914505

Dania Sagheer, Fadel Sukkar . A Hybrid Intelligent System for Abstractive Summarization. International Journal of Computer Applications. 168, 9 ( Jun 2017), 37-44. DOI=10.5120/ijca2017914505

@article{ 10.5120/ijca2017914505,
author = { Dania Sagheer, Fadel Sukkar },
title = { A Hybrid Intelligent System for Abstractive Summarization },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 168 },
number = { 9 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 37-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume168/number9/27904-2017914505/ },
doi = { 10.5120/ijca2017914505 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:15:42.097630+05:30
%A Dania Sagheer
%A Fadel Sukkar
%T A Hybrid Intelligent System for Abstractive Summarization
%J International Journal of Computer Applications
%@ 0975-8887
%V 168
%N 9
%P 37-44
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we present a new technique for abstractive summarization of Arabic texts. a system of knowledge base and fuzzy logic has been designed and implemented to simulate human ability of understanding the content of Arabic text, and to create abstractive summary for this text. The knowledge base has been designed for financial and economic field. It consists of facts and if-then rules. The sentences have been parsed by previous stage. The sentences of summary have been obtained using knowledge based system, then Fuzzy system has been designed for selecting appropriate summary of sentences. General membership function has been designed to obtain all the mathematical shapes of membership functions. The peak of the membership function has been designed for hierarchy relations of concepts, and for the destination of semantic relations. The edges of the function has been designed for semantic relations of concepts, and for the domain of semantic relations. The system has been tested on texts for different subjects. The texts have been taken from EASC University Corpus (Essex Arabic Summaries Corpus). The results of this research have shown the effectiveness of the novel hybrid system in terms of semantic, meaning and right composition.

References
  1. Binwahlan, S. M., "Extractive Summarization Method for Arabic Text - ESMAT", International Journal of Computer Trends and Technology (IJCTT) V21(2):103-109, March 2015.
  2. Nenkova, A. and McKeown, K., “Automatic Summarization”, Foundations and Trends in Information Retrieval Vol. 5, Nos. 2–3 (2011) 103–233.
  3. Genest, E. P. and Lapalme, G. 2011. Framework for Abstractive Summarization using Text-to-Text Generation. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pages 64–73.
  4. Kwaik, A. K. 2011 Automatic Arabic Text Summarization System (AATSS) Based on Semantic Feature Extraction. Master Thesis. Information Technology, University of Gaza.
  5. Kasture, N. R., Yargal, N., Singh, N.N., Kulkarni, N. and Mathur, V., “A Survey on Methods of Abstractive Text Summarization”, International Journal for Research in Emerging Science and Technology, Volume-1, Issue-6, November-2014.
  6. Gaikwad, K. D. and Mahender, N. C., “ A Review Paper on Text Summarization”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 5, Issue 3, March 2016.
  7. Khan, A. and Salim, N., "A Review on Abstractive Summarization Methods", Journal of Theoretical and Applied Information Technology, 2014.
  8. Banerjee, S., Mitra, P. and Sugiyama, K. 2015. Multi-Document Abstractive Summarization Using ILP Based Multi-Sentence Compression. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI).
  9. Imam, I., Nounou, N., Hamouda, A. and Abdul Khalek, A. H. 2013, Query based Arabic Text Summarization, International Journal of Computer Science & Technology, vol /4/, Issue /2/.
  10. Arabic Corpora. Essex Arabic Summaries Corpus: http://www.essex.ac.uk/linguistics/research/arabic/arabiccorpora/easc.aspx
Index Terms

Computer Science
Information Sciences

Keywords

Abstractive Summarization Knowledge Base Fuzzy Logic