Open AccessRETRIEVAL PERFORMANCE OF ARABIC LIGHT STEMMERS
Author(s) -
Saoudi Ouahiba,
Roslina Othman
Publication year - 2019
Publication title -
international journal of modern trends in social sciences
Language(s) - English
Resource type - Journals
ISSN - 2600-8777
DOI - 10.35631/ijmtss.210008
Subject(s) - arabic , computer science , artificial intelligence , information retrieval , natural language processing , philosophy , linguistics
Despite the fact that stemming greatly improves Arabic information retrieval performance, yet no standard stemmer emerges in the field of Arabic IR due to some limitations and shortcomings. Among the recurring problems is that the stemmer can reduce unrelated words to the same stem as well as fall short to reduce related words to a common stem. Many studies have suggested Arabic algorithms to address the problem associated with stemming. This paper aims to review the state of the retrieval performance of Arabic Light stemmers based on the main objectives achieved, causes for retrieval success and failure, retrieval measure, the affixes, and methodologies. The results showed that light 10 has better retrieval performance compared to other reviewed Arabic light stemmers.