Wajeez: An Extractive Automatic Arabic Text Summarisation System

The volume of Arabic information is rapidly increasingly nowadays, and thus, access to the corrects is arguably one of the most difficult research problems facing readers and researchers. Text Summarisation Systems are utilised to produce a short text describing significant portions of the original text. That is by selecting the most important sentences, following several steps: preprocessing, stemming, scoring, and summary extraction. Nevertheless, summarisation systems remain still in their infancy for the Arabic language. Therefore, this paper proposes an automatic Arabic text summarisation systems, entitled Wajeez, that introduces a new inclusive scoring formula that generates a final summary from several top-ranking sentences. Wajeez was applied on two different datasets: the Essex Arabic Summaries Corpus (EASC) and a manual summary to assess its performance using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) set of metrics. In comparison to two other competitions systems, Wajeez performed comparatively well when a title is provisioned to support summarisation.