Author

Nada Ghneim, Waseem Safi, Moayad Al Said Ali

Published in

Conference Paper, Conference: The International Business Information Management Conference (13th IBIMA), Arabic Information Processing, At Marrakech, Morocco, November 2009

Abstract

This paper presents the ArOntoLearn a Framework for Arabic Ontology learning from textual resources. Supporting Arabic language and using domain knowledge or previous knowledge in the learning process are the main features of our framework, besides it represents the learned ontology in Probabilistic Ontology Model (POM), which can be translated into any knowledge representation formalism, and implements data-driven change discovery, therefore it updates the POM according to the corpus changes only, and allows user to trace the evolution of the ontology with respect to the changes in the underlying corpus. Our framework analyses Arabic textual resources, and matches them to Arabic Lexico-syntactic patterns in order to learn new Concepts and Relations.

Keywords: Ontologies, Ontology Learning, Knowledge Acquisition, Arabic Natural Language Processing.

Link to read full paper

https://www.researchgate.net/publication/284323056_Building_a_Framework_for_Arabic_Ontology_Learning