Ontology Mapping based on Similarity Measure and Fuzzy Logic
MetadataShow full item record
In this paper, we present a method of an ontology mapping based on a similarity measure and Fuzzy logic in order to classify (i) the similarity of the ontology structure of learning object repositories and (ii) LOR which stores metadata of learning objects based on our ontology model. In this model, values of the ontology similarity are computed for concepts, properties, and relations. The ontology similarity uses parameters based on the Fuzzy Control Language (FCL) which consists of a fuzzy set of the ontology similarity ("Less", "Same", "More"), 7 classes of ontology similarity, and rules of the classification of ontologies. The formula of similarity measure by the Jaccard's coefficient is applied to map a similarity of ontology structures. At the end of the article, we show an experience of implementation this model as a prototype.
Proceedings of E-Learn 2007
© AACE. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Reprinted from the Proceedings of E-Learn 2007 with permission of AACE (http://www.aace.org).