Azzeddine Mazroui

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In this paper, we present an Arabic morphological analysis system that assigns, for each word of an unvoweled Arabic sentence, a unique root depending on the context. The proposed system is composed of two modules. The first one consists of an analysis out of context. In this module, we segment each word of the sentence into its elementary morphological(More)
Hybrid approaches for automatic vowelization of Arabic texts are presented in this article. The process is made up of two modules. In the first one, a morphological analysis of the text words is performed using the open source morphological Analyzer AlKhalil Morpho Sys. Outputs for each word analyzed out of context, are its different possible vowelizations.(More)
This work falls within the framework of the Natural Language Processing. Its objective is to assess the level of ambiguity caused by the absence of diacritical marks in Arabic texts during the information extraction process. We have carried out a statistical study based on four indicators: the root, the lemma, the stem and the POS tag of the word. For this,(More)
We present in this work a new approach for the Automatic diacritization for Arabic texts using three stages. During the first phase, we integrated a lexical database containing the most frequent words of Arabic with morphological analysis by Alkhalil Morpho Sys which provided possible diacritization for each word. The objective of the second module is to(More)
In this paper we propose a new recognition approach for Arabic numerals. Given that the performance of recognition systems for Arabic numerals are closely linked to the choice of features and classification system used in the recognition phase, we seek to exploit the possibilities of the theory of Bézier curves that allows representing parametric curves(More)
Despite the recognition of the Arabic language by the United Nations and its active development, there are no powerful interactive dictionaries to accompany efficiently this development. In addition, most of the existing dictionaries require knowledge of morphological rules to get the meaning of words. We studied in this paper the “Interactive Dictionary of(More)
Stemming is the main step used for handling the morphologically rich languages such as Arabic. It is usually used in several fields such as Natural Language Processing, Information Retrieval (IR), and Text Mining. The goal of stemming is reducing inflected or derived words to their base (root or stem), from a generally written word form. Considering that(More)
The recognition of Arabic characters is still a major challenge to overcome. In this paper, we propose a new approach in the field of recognition of multifont isolated Arabic characters. It is based on the semi-cursive nature of Arabic characters and consists in assimilating them to a small number of checkpoints equipped with their derivatives. The choice(More)
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