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Automatic Persian Text Summarization Using Linguistic Features from Text Structure Analysis

Ebrahim Heidary1, Hamïd Parvïn2,3,4,*, Samad Nejatian5,6, Karamollah Bagherifard1,6, Vahideh Rezaie6,7
1 Department of Computer Engineering, Yasooj Branch, Islamic Azad University, Yasooj, Iran
2 Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam
3 Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Vietnam
4 Department of Computer Science, Nourabad Mamasani Branch, Islamic Azad University, Mamasani, Iran
5 Department of Electrical Engineering, Yasooj Branch, Islamic Azad University, Yasooj, Iran
6 Young Researchers and Elite Club, Yasooj Branch, Islamic Azad University, Yasooj, Iran
7 Department of Mathematics, Yasooj Branch, Islamic Azad University, Yasooj, Iran
* Corresponding Author: Hamïd Parvïn. Email:

Computers, Materials & Continua 2021, 69(3), 2845-2861. https://doi.org/10.32604/cmc.2021.014361

Received 16 September 2020; Accepted 03 February 2021; Issue published 24 August 2021

Abstract

With the remarkable growth of textual data sources in recent years, easy, fast, and accurate text processing has become a challenge with significant payoffs. Automatic text summarization is the process of compressing text documents into shorter summaries for easier review of its core contents, which must be done without losing important features and information. This paper introduces a new hybrid method for extractive text summarization with feature selection based on text structure. The major advantage of the proposed summarization method over previous systems is the modeling of text structure and relationship between entities in the input text, which improves the sentence feature selection process and leads to the generation of unambiguous, concise, consistent, and coherent summaries. The paper also presents the results of the evaluation of the proposed method based on precision and recall criteria. It is shown that the method produces summaries consisting of chains of sentences with the aforementioned characteristics from the original text.

Keywords

Natural language processing; extractive summarization; linguistic feature; text structure analysis

Cite This Article

E. Heidary, H. Parvïn, S. Nejatian, K. Bagherifard and V. Rezaie, "Automatic persian text summarization using linguistic features from text structure analysis," Computers, Materials & Continua, vol. 69, no.3, pp. 2845–2861, 2021.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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