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Article type: Research Article
Authors: Abouenour, Lahsen | Nasri, Mohamed | Bouzoubaa, Karim | Kabbaj, Adil | Rosso, Paolo
Affiliations: Computer Science Department, Mohammadia School of Engineers, Mohammed V-Agdal University, Rabat, Morocco | Computer Science Department, INSEA, Rabat, Morocco | NLE Lab, PRHLT Research Center, Universitat Politècnica de València, València, Spain
Note: [] Corresponding author. Lahsen Abouenour, Computer Science Department, Mohammadia School of Engineers, Mohammed V-Agdal University, Rabat, Morocco. Tel.: +212 6 62385800; E-mail: abouenour@yahoo.fr
Abstract: The last decade had known a great interest in Arabic Natural Language Processing (NLP) applications. This interest is due to the prominent importance of this 6th most wide-spread language in the world with more than 350 million native speakers. Currently, some basic Arabic language challenges related to the high inflection and derivation, Part-of-Speech (PoS) tagging, and diacritical ambiguity of Arabic text are practically tamed to a great extent. However, the development of high level and intelligent applications such as Question Answering (QA) systems is still obstructed by the lacks in terms of ontologies and other semantic resources. In this paper, we present the construction of a new Arabic ontology leveraging the contents of Arabic WordNet (AWN) and Arabic VerbNet (AVN). This new resource presents the advantage to combine the high lexical coverage and semantic relations between words existing in AWN together with the formal representation of syntactic and semantic frames corresponding to verbs in AVN. The Conceptual Graphs representation was adopted in the framework of a multi-layer platform dedicated to the development of intelligent and multi-agents systems. The built ontology is used to represent key concepts in questions and documents for further semantic comparison. Experiments conducted in the context of the QA task show a promising coverage with respect to the processed questions and passages. The obtained results also highlight an improvement in the performance of Arabic QA regarding the c@1 measure.
Keywords: Ontology, conceptual graphs, Arabic natural language processing, question answering, WordNet, VerbNet
DOI: 10.3233/IFS-141248
Journal: Journal of Intelligent & Fuzzy Systems, vol. 27, no. 6, pp. 2869-2881, 2014
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