Abstract-This paper presents a semiautomatic framework that aims to produce domain concept maps from text and then to derive domain ontologies from these concept maps. This methodology particularly targets the e-learning and Artificial Intelligence in Education (AIED) communities as they need such structures to sustain the production of e-learning resources tailored to learners' needs. This paper details the steps to transform textual resources, particularly textual learning objects (LOs), into domain concept maps, and it explains how this abstract structure is transformed into a formal domain ontology. A methodology is also presented to evaluate the results of ontology learning. The paper shows how such structures (domain concept maps and formal ontologies) make it possible to bridge the gap between e-learning and Intelligent Tutoring Systems by providing a common domain model. Index Terms-Applications and expert knowledge-intensive systems (education), intelligent Web services and Semantic Web knowledge acquisition, knowledge reuse.
Amal zouaq et al. REF proposes a methodology to transform Textual Resources and learning Objects to concept maps and derive domain ontologies from Concept maps.
Building Domain Ontologies from Text for Educational Purposes
IEEE Transactions on Learning Technologies
IEEE Transactions on Learning Technologies
Computer Science