A Meronomic Relatedness Measure for Domain Ontologies Using Concept Probability and Multiset Theory
Journal or Book Title
2009 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY
Semantic relatedness measures provide a means to determine how closely related two concepts may or may not be. In the area of ontology alignment, many lexical-based relatedness measures have been successfully applied within the realm of domain ontologies. The alignment initiative, however, has not included all measures of relatedness. More generic measures of relatedness, such as meronomy-based, have yet to be established beyond lexical ontologies. This paper introduces an algorithm for measuring meronomic relatedness between concepts within a domain ontology. Specifically, a new method is proposed for measuring how much one concept is ldquopart ofrdquo another in a domain ontology. This is accomplished by utilizing inherent attributes of these ontologies in concert with protocols currently applied in established relatedness measures. Key features of this method include a unique approach to the weighted edge measure, one in which each edge is weighted based on applying a concept probability algorithm to a multiset composed of ontology property ranges. The application of this method is then illustrated with the aid of two case-studies, namely a camera ontology and a wine ontology, and the results are discussed.
Witherell, P; Krishnamurty, S; Grosse, I; and Wileden, J, "A Meronomic Relatedness Measure for Domain Ontologies Using Concept Probability and Multiset Theory" (2009). 2009 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY. 1263.