Intelligent model for automatic text summarization

• Main Authors: Binwahlan, Mohammed Salem, Salim, Naomie, Suanmali, Ladda
• Format: Article
• Published: Asian Network for Scientific Information 2009
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/12893/; http://dx.doi.org/10.3923/itj.2009.1249.1255
• Institution: Universiti Teknologi Malaysia

The navigation through hundreds of the documents in order to find the interesting information is a tough job and waste of the time and effort. Automatic text summarization is a technique concerning the creation of a compressed form for single document or multi-documents for tackling such problem. In this study, we introduced an intelligent model for automatic text summarization problem; we tried to exploit different resources advantages in building of our model like advantage of diversity based method which can filter the similar sentences and select the most diverse ones and advantage of the non diversity method used in this study which is the adaptation of intelligent techniques like fuzzy logic and swarm intelligence for building that method which gave it a good ability for picking up the most important sentences in the text. The experimental results showed that our model got the best performance over all methods used in this study.