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Summarising text with a genetic algorithm-based sentence extraction

Qazvinian, V ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1504/IJKMS.2008.019750
  3. Publisher: 2008
  4. Abstract:
  5. Automatic text summarisation has long been studied and used. The growth in the amount of information on the web results in more demands for automatic methods for text summarisation. Designing a system to produce human-quality summaries is difficult and therefore, many researchers have focused on sentence or paragraph extraction, which is a kind of summarisation. In this paper, we introduce a new method to make such extracts. GeneticAlgorithm (GA)-based sentence selection is used to make a summary, and once the summary is created, it is evaluated using a fitness function. The fitness function is based on three following factors: Readability Factor (RF), Cohesion Factor (CF) and Topic-Relation Factor (TRF). In this paper, we introduce these factors and discuss the Genetic Algorithm with the specific fitness function. Evaluation results are also shown and discussed in the paper. © 2008 Inderscience Enterprises Ltd
  6. Keywords:
  8. Source: International Journal of Knowledge Management Studies ; Volume 2, Issue 4 , 2008 , Pages 426-444 ; 17438268 (ISSN)
  9. URL: http://www.inderscience.com/offer.php?id=19750