@Article{, title={Bio-inspired approaches for extractive document summarization:A comparative study}, author={Rasmita Rautraya,*, Rakesh Chandra Balabantarayb}, journal={Karbala International Journal of Modern Science مجلة كربلاء العالمية للعلوم الحديثة}, volume={3}, number={3}, pages={119-130}, year={2017}, abstract={With the exponential growth of information in World Wide Web, extracting relevant information from huge amount of data hasbecome a critical task. Text summarization has been appeared as one of the solution to such problem. As the main objective is toretrieve a condensed document that pertain the original information, so it can be considered as an optimization problem. In thispaper, a comparative analysis of few meta-heuristic approaches such as Cuckoo Search (CS), Cat Swarm Optimization (CSO),Particle Swarm Optimization (PSO), Harmony Search (HS), and Differential Evolution (DE) algorithm is presented for singledocument summarization problem. The performance of all these algorithms are compared in terms of different evaluation metricssuch as F score, true positive rate and positive predicate value to validate summary relevancy and non-redundancy over traditionaland standard Document Understanding Conference (DUC) datasets.

} }