GDL

Journal from gdlhub / 2022-02-12 16:32:58
Oleh : Chouaib Moukrim, Tragha Abderrahim, El Habib Benlahmer, Almalki Tarik, King Saud University
Dibuat : 2022-02-12, dengan 0 file

Keyword : Arabic, Syntactic errors, Natural language processing, Ontology
Url : http://www.sciencedirect.com/science/article/pii/S1319157818310012
Sumber pengambilan dokumen : web

Natural Language Processing (NLP) has been a growing area of research in computer and cognitive sciences, using experimental approaches. Morphology and syntax play specifically a vital role in the correct interpretation of a sentence. In this paper, we will present a syntactic error correction system based on the automatic generation of correct sentences in Arabic. First, we extract the words from the considered sentence and we then generate all the possible sentences that are syntactically correct; based on a logical description of the rules of Arabic grammar in the ontology. We will afterwards compare the original sentence with the generated sentences to detect any eventual errors followed by the correction phase. In case the system has not found a sentence that looks similar to the original sentence, the correct alternative sentences are automatically offered. The use of the Arabic syntactic corrector can increase productivity and improve the quality of the text for anyone who writes in the Arabic language. Successful tests have been performed using a set of Arabic sentences. The implemented system achieved a precision rate of about 92% and a recall rate of about 84%. By observing the achieved results, it is concluded that our approach is promising.

Deskripsi Alternatif :

Natural Language Processing (NLP) has been a growing area of research in computer and cognitive sciences, using experimental approaches. Morphology and syntax play specifically a vital role in the correct interpretation of a sentence. In this paper, we will present a syntactic error correction system based on the automatic generation of correct sentences in Arabic. First, we extract the words from the considered sentence and we then generate all the possible sentences that are syntactically correct; based on a logical description of the rules of Arabic grammar in the ontology. We will afterwards compare the original sentence with the generated sentences to detect any eventual errors followed by the correction phase. In case the system has not found a sentence that looks similar to the original sentence, the correct alternative sentences are automatically offered. The use of the Arabic syntactic corrector can increase productivity and improve the quality of the text for anyone who writes in the Arabic language. Successful tests have been performed using a set of Arabic sentences. The implemented system achieved a precision rate of about 92% and a recall rate of about 84%. By observing the achieved results, it is concluded that our approach is promising.

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