Towards author identification of Arabic text articles

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.