Genetic Approach for Arabic Part of Speech Tagging

With the growing number of textual resources available, the ability to understand them becomes critical. An essential first step in understanding these sources is the ability to identify the parts-of-speech in each sentence. Arabic is a morphologically rich language, which presents a challenge for part of speech tagging. In this paper, our goal is to propose, improve, and implement a part-of-speech tagger based on a genetic algorithm. The accuracy obtained with this method is comparable to that of other probabilistic approaches.