Genetic approach for arabic part of speech tagging

TL;DR

This paper proposes a genetic algorithm-based method for Arabic part of speech tagging, addressing the language's morphological complexity and achieving accuracy comparable to probabilistic models.

Contribution

It introduces a novel genetic algorithm approach for Arabic POS tagging, improving upon existing methods for this morphologically rich language.

Findings

Accuracy comparable to probabilistic approaches

Effective handling of Arabic morphological complexity

Demonstrated feasibility of genetic algorithms for POS tagging

Abstract

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 part of speech in each sentence. Arabic is a morphologically rich language, wich 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 alorithm. The accuracy obtained with this method is comparable to that of other probabilistic approaches.