Automatic text summarization is a process to reduce the volume of text documents using computer programs to create a text summary with keeping the key terms of the documents. Due to cumulative growth of information and data, automatic text summarization technique needs to be applied in various domains. The approach helps in decreasing the quantity of the document without changing the context of information. In this paper, the proposed Persian text summarizer system employs combination of graph-based and the TF-IDF methods after word stemming in order to weight the sentences. SA-GA based sentence selection is used to make a summary, and once the summary is created. The SA-GA is a hybrid algorithm that combines Genetic Algorithm (GA) and Simulated Annealing (SA). The fitness function is based on three following factors: Readability Factor, Cohesion Factor, and Topic-Relation Factor. Evaluation results demonstrated the efficiency of the proposed system.
| Published in |
International Journal of Intelligent Information Systems (Volume 3, Issue 6-1)
This article belongs to the Special Issue Research and Practices in Information Systems and Technologies in Developing Countries |
| DOI | 10.11648/j.ijiis.s.2014030601.26 |
| Page(s) | 84-90 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Automatic Text Summarization, Stemming, TF-IDF, Genetic Algorithm, Simulated Annealing
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APA Style
Elham Mahdipour, Masoumeh Bagheri. (2014). Automatic Persian Text Summarizer Using Simulated Annealing and Genetic Algorithm. International Journal of Intelligent Information Systems, 3(6-1), 84-90. https://doi.org/10.11648/j.ijiis.s.2014030601.26
ACS Style
Elham Mahdipour; Masoumeh Bagheri. Automatic Persian Text Summarizer Using Simulated Annealing and Genetic Algorithm. Int. J. Intell. Inf. Syst. 2014, 3(6-1), 84-90. doi: 10.11648/j.ijiis.s.2014030601.26
AMA Style
Elham Mahdipour, Masoumeh Bagheri. Automatic Persian Text Summarizer Using Simulated Annealing and Genetic Algorithm. Int J Intell Inf Syst. 2014;3(6-1):84-90. doi: 10.11648/j.ijiis.s.2014030601.26
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Download@article{10.11648/j.ijiis.s.2014030601.26,
author = {Elham Mahdipour and Masoumeh Bagheri},
title = {Automatic Persian Text Summarizer Using Simulated Annealing and Genetic Algorithm},
journal = {International Journal of Intelligent Information Systems},
volume = {3},
number = {6-1},
pages = {84-90},
doi = {10.11648/j.ijiis.s.2014030601.26},
url = {https://doi.org/10.11648/j.ijiis.s.2014030601.26},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.s.2014030601.26},
abstract = {Automatic text summarization is a process to reduce the volume of text documents using computer programs to create a text summary with keeping the key terms of the documents. Due to cumulative growth of information and data, automatic text summarization technique needs to be applied in various domains. The approach helps in decreasing the quantity of the document without changing the context of information. In this paper, the proposed Persian text summarizer system employs combination of graph-based and the TF-IDF methods after word stemming in order to weight the sentences. SA-GA based sentence selection is used to make a summary, and once the summary is created. The SA-GA is a hybrid algorithm that combines Genetic Algorithm (GA) and Simulated Annealing (SA). The fitness function is based on three following factors: Readability Factor, Cohesion Factor, and Topic-Relation Factor. Evaluation results demonstrated the efficiency of the proposed system.},
year = {2014}
}
TY - JOUR T1 - Automatic Persian Text Summarizer Using Simulated Annealing and Genetic Algorithm AU - Elham Mahdipour AU - Masoumeh Bagheri Y1 - 2014/11/06 PY - 2014 N1 - https://doi.org/10.11648/j.ijiis.s.2014030601.26 DO - 10.11648/j.ijiis.s.2014030601.26 T2 - International Journal of Intelligent Information Systems JF - International Journal of Intelligent Information Systems JO - International Journal of Intelligent Information Systems SP - 84 EP - 90 PB - Science Publishing Group SN - 2328-7683 UR - https://doi.org/10.11648/j.ijiis.s.2014030601.26 AB - Automatic text summarization is a process to reduce the volume of text documents using computer programs to create a text summary with keeping the key terms of the documents. Due to cumulative growth of information and data, automatic text summarization technique needs to be applied in various domains. The approach helps in decreasing the quantity of the document without changing the context of information. In this paper, the proposed Persian text summarizer system employs combination of graph-based and the TF-IDF methods after word stemming in order to weight the sentences. SA-GA based sentence selection is used to make a summary, and once the summary is created. The SA-GA is a hybrid algorithm that combines Genetic Algorithm (GA) and Simulated Annealing (SA). The fitness function is based on three following factors: Readability Factor, Cohesion Factor, and Topic-Relation Factor. Evaluation results demonstrated the efficiency of the proposed system. VL - 3 IS - 6-1 ER -
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