An Improved General Purpose Arabic Morphological Analyzer and Generator Model (GPAM)

Abstract

Although, morphological analysis is a vital part of natural language processing applications, there are no definitive standards for evaluating and benchmarking Arabic morphological systems. This paper proposes assessment criteria for evaluating Arabic morphological systems by scrutinizing the input, output and architectural design to enables researchers to evaluate and fairly compare Arabic morphology systems. By scoring some state of the art Arabic morphological analyzers based on the proposed criteria; the accuracy scores showed that the best algorithm failed to achieve a reliable rate. Hence, this paper introduced an enhanced algorithm for resolving the inflected Arabic word, identifies its root, finds its pattern and POS tagging that will reduce the search time considerably and to free up the deficiencies identified by this assessment criteria. The proposed model uses semantic rules of the Arabic language on top of a hybrid sub-model based on two existing algorithms (Al-Khalil & IAMA rules). Based on applying the proposed assessment criteria the efficiency and speed have been enhanced where the system achieved up to 1500 words per second in small text up to 3000 words per second in larger documents