Exploiting the Arabic Wikipedia for semi-automatic construction of a lexical ontology

Authors:
Mohamed Mahdi Boudabous;Lamia Hadrich Belguith;Fatiha Sadat
Affiliations:
ANLP Research Group, MIRACL Laboratory, Faculty of Economics and Management of Sfax, Sfax, Tunisia;ANLP Research Group, MIRACL Laboratory, Faculty of Economics and Management of Sfax, Sfax, Tunisia;Department of Computer Science, University of Quebec in Montreal UQAM, Montreal, Canada
Venue:
International Journal of Metadata, Semantics and Ontologies
Year:
2013

Citing 7
Cited 0

Discovery of ontologies from knowledge bases

Proceedings of the 1st international conference on Knowledge capture
Ontology Learning for the Semantic Web

IEEE Intelligent Systems
Ontological Reengineering for Reuse

EKAW '99 Proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management
Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information

DS-8 Proceedings of the IFIP TC2/WG2.6 Eighth Working Conference on Database Semantics- Semantic Issues in Multimedia Systems
YAGO: A Large Ontology from Wikipedia and WordNet

Web Semantics: Science, Services and Agents on the World Wide Web
DBpedia: a nucleus for a web of open data

ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
BabelNet: building a very large multilingual semantic network

ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a hybrid numerical/linguistic method to build a lexical ontology for the Arabic language. This method is based on the Arabic Wikipedia. It consists of two phases: analysing the description section in order to build core ontology and then using the physical structure of Wikipedia articles info-boxes, category pages and redirect links and their contents for enriching the core ontology. The building phase of the core ontology is implemented via the TBAO system. The obtained core ontology contains more than 200,000 concepts.