Arabic Text Summary Evaluation Method

This paper presents an automatic method tier assessing Arabic text summaries. This method is based on a machine learning approach which operates by building a model that combines multiple features to predict the human score "Overall Responsiveness" of an unseen summary. We have tested multiple single and ensemble learning classifiers to build the best predictive model. We experimented our method in summary level evaluation where we evaluate the quality of each text summary separately and in a system level evaluation where the average quality of the text summary system was calculated. We report in this paper the results of our experiments for both evaluation levels; our results prove that the proposed method outperforms the baselines on both tasks.