Intelligent Agents for the Semantic Annotation of Educational Resources
Aziz ORICHE1, Abderrahman CHEKRY2, Mohamed KHALDI3
1Aziz Oriche, Université Abdelmalek Essaâdi, Laboratoire, LIROSA & LNTE, Tétouan, Maroc.
2Abderrahman Chekry, Université Abdelmalek Essaâdi, Laboratoire, LIROSA & LNTE, Tétouan, Maroc.
3MOHAMED KHALDI, Université Abdelmalek Essaâdi, Laboratoire, LIROSA & LNTE, Tétouan, Maroc.
Manuscript received on October 20, 2013. | Revised Manuscript received on November 01, 2013. | Manuscript published on November 05, 2013. | PP: 96-104 | Volume-3 Issue-5, November 2013. | Retrieval Number: E1907113513/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Our objective is to describe the content of educational resources semantically annotating with unambiguous information to facilitate the exploitation of these resources by software agents, these resources are delimited by tags (XHTML, XML), and are well structured. We propose a semantic annotation system based on three intelligent agents to manage semantic annotations educational resources, these annotations are guided by domain ontology. The domain ontology contains a set of concepts, relationships between these concepts and their properties. Each concept of ontology some have one or more (synonyms) to represent words. All these terms are used to describe instances of a domain concept; these terms are more focused in the description of concepts. All these concepts are validated by the domain expert. Taking into account that the teaching materials are in HTML or XML whose structure is a DOM (Document Object Model) we seek to identify the terms of educational concepts in the nodes of the tree, extract all these concepts while respect of the domain ontology. The terms or educational concepts candidates are associated with terms and concepts of the ontology to determine appropriate concepts to annotate nodes in which they are located.
Keywords: Semantic Annotation, Metadata, Multi-agent systems, Ontology.