Towards author identification of Arabic text articles
Ahmed Fawzi Otoom, Emad E. Abdullah, Shifaa Jaafer, Aseel Hamdallh, Dana Amer · 2014
We target the problem of identifying the author of an Arabic text article. Our main aim is to develop an intelligent system that is capable of classifying a new article into one of seven classes that belong to seven different authors. For this purpose, we propose a novel dataset consisting of 12 features and 456 instances belonging to the 7 authors. In addition, we combine the proposed feature set with strong classification algorithms to assist in distinguishing between the different authors. Our results show that the proposed dataset has proved successful with a classification performance accuracy of 82% with the hold-out test.