Pruning Concept Map to Geneate Ontology
Knowledge representation in the form of a concept map can be a good idea to categorize domain terms and their relations and help to generate ontology. Supplementing detail information to and pruning useless data from the concept map, which likes a skeleton in evolving ontology, can be semantically a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Iran Telecom Research Center
2017-03-01
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| Series: | International Journal of Information and Communication Technology Research |
| Subjects: | |
| Online Access: | http://ijict.itrc.ac.ir/article-1-49-en.html |
| Summary: | Knowledge representation in the form of a concept map can be a good idea to categorize domain terms and their relations and help to generate ontology. Supplementing detail information to and pruning useless data from the concept map, which likes a skeleton in evolving ontology, can be semantically accomplished using the domain knowledge. In this paper, we propose a method using structural knowledge resources as well as tacit knowledge of experts to generate the ontology of eLearning domain. The concept map of eLearning is manually improved and finally verified using the group of eLearning experts. In order to enrich the ontology with merging into upcoming terms, the paper proposed an automatic method based on two external knowledge sources, Wikipedia and WordNet. The semantic similarity of concepts which is measured using the words hierarchy of WordNet combined with relations of concepts extracted from the Wikipedia graph is applied to link the new eLearning concepts to the domain ontology. The generated ontology is a dynamic knowledge source which can improve itself gradually. This integrated knowledge of eLearning domain can be used to model educational activities and to build, organize, and update specific learning resources. |
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| ISSN: | 2251-6107 2783-4425 |