Arabic Single-Document Text Summarization Using Particle Swarm Optimization Algorithm

In this research, we propose the use of Particle Swarm Optimization (PSO) algorithm for the extraction of summaries for single Arabic documents. The PSO approach is compared with evolutionary approaches that use Genetic Algorithms (GA) and Harmony Search (HS). The Essex Arabic Summaries Corpus (EASC) and the Recall-Oriented Understanding for Gisting Evaluation (ROUGE) tool are used to evaluate the proposed approach. Experimental results showed that the proposed approach achieved competitive and even higher ROUGE scores in comparison to HS and GA approaches in the state-of-the-art.