Volume 28, Issue 1 (IJIEPR 2017)                   IJIEPR 2017, 28(1): 75-84 | Back to browse issues page



DOI: 10.22068/ijiepr.28.1.75

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MirShojaee H, Masoumi B, Zeinali E. Biogeography-Based Optimization Algorithm for Automatic Extractive Text Summarization . IJIEPR. 2017; 28 (1) :75-84
URL: http://ijiepr.iust.ac.ir/article-1-722-en.html

Dr. Department of Computer and information technology Engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran , .
Abstract:   (608 Views)

    Given the increasing number of documents, sites, online sources, and the users’ desire to quickly access information, automatic textual summarization has caught the attention of many researchers in this field. Researchers have presented different methods for text summarization as well as a useful summary of those texts including relevant document sentences. This study selects extractive method out of different summarizing methods (e.g. abstract method). Extractive method involves summarizing text through objective extraction of some parts of a text like word, sentence, and paragraph. A summarization issue would be unsolvable by exact methods in a reasonable time with considering documents with high amount of information (NP complete). These kinds of issues are usually solved using metaheuristic methods. A biogeography-based optimization algorithm (BBO), which is a new metaheuristic method in the domain of extractive text summarization, is used in this article. 

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Highlights:

  • Text summarization, using metaheuristic Biogeography-Based Optimization (BBO) algorithm with a focus on extractive features of texts.
  • Implementation of Biogeography-Based Optimization (BBO) on standard 100,200,400 -word documents DUC2002. 
  • Comparison of the proposed method with other methods indicates that evaluation of precision, recall, and score show more improvement than those in the GA, PSO, BFOA  methods.


Type of Study: Research | Subject: Optimization Techniques
Received: 2017/03/6 | Accepted: 2017/06/11 | Published: 2017/06/18

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