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In spite of its robust syntax, semantic cohesion, and less ambiguity, lemmalevel analysis and generation does not yet focused in Arabic NLP literatures.In the current research, we propose the first non-statistical accurate Arabiclemmatizer algorithm that is suitable for information retrieval (IR) systems.The proposed lemmatizer makes use of different Arabic language knowledgeresources to generate accurate lemma form and its relevant features thatsupport IR purposes. As a POS tagger, the experimental results show that, theproposed algorithm achieves a maximum accuracy of 94.8%. For first seendocuments, an accuracy of 89.15% is achieved, compared to 76.7% of up to dateStanford accurate Arabic model, for the same, dataset.

An Accurate Arabic Root-Based Lemmatizer for Information Retrieval Purposes