Mohammadamin Shirvani - PhD student in computer engineering - network and computing, Islamic Azad University, South Tehran branch
Fardin Soleimani - PhD Candidate in computer engineering - Artificial Intelligence, Islamic Azad University, South Tehran branch
Mozhdeh Tanha - PhD in computer science-soft computing and artificial intelligence, Islamic Azad University, South Tehran branch,

Today, with rapid growth of the World Wide Web and creation of Internet sites and online text resources, text summarization issue is highly attended by various researchers. Extractive-based text summarization is an important summarization method which is included of selecting the top representative sentences from the input document. When, we are facing into large data volume documents, the extractive-based text summarization seems to be an unsolvable problem. Therefore, to deal with such problems, meta-heuristic techniques are applied as a solution. In this paper, we used Cuckoo Search Optimization Algorithm (CSOA) to improve performance of extractive-based summarization method. The proposed approach is examined on Doc. ۲۰۰۲ standard documents and analyzed by Rouge evaluation software. The obtained results indicate better performance of proposed method compared with other similar techniques.

Persian Text summarization, Extractive method, Cuckoo Search Optimization algorithm