Abstract
Ontologies are a crucial tool for formally specifying the vocabulary and the concepts of agent platforms, so, to share information, agents that use different vocabularies must be able to translate data from one ontological framework to another. The treatment of uncertainty plays a key role in the ontology mapping, as the degree of overlapping between concepts can not be represented logically. This paper aims to provide mechanisms to support experts in the first steps of the ontology mapping process using fuzzy logic techniques to determine the similarity between concepts from different ontologies. For each pair of concepts, two types of similarity are calculated: the first using the Jaccard coefficient, based on relevant documents taken from the web, and the second based on the linguistic relationship of concepts. Finally, the similarity is calculated through a fuzzy rule-based system. The ideas presented in this work are validated using two real-world ontologies.
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Fernández, S., Velasco, J.R., López-Carmona, M.A. (2009). A Fuzzy Rule-Based System for Ontology Mapping. In: Yang, JJ., Yokoo, M., Ito, T., Jin, Z., Scerri, P. (eds) Principles of Practice in Multi-Agent Systems. PRIMA 2009. Lecture Notes in Computer Science(), vol 5925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11161-7_35
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DOI: https://doi.org/10.1007/978-3-642-11161-7_35
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