Abstract
Ontology alignment (or matching) is the operation that takes two ontologies and produces a set of semantic correspondences (usually semantic similarities) between some elements of one of them and some elements of the other. A rigorous, efficient and scalable similarity measure is a pre-requisite of an ontology alignment process. This paper presents a semantic similarity measure based on a matrix represention of nodes from an RDF labelled directed graph. An entity is described with respect to how it relates to other entities using N-dimensional vectors, being N the number of selected external predicates. We adapt a known graph matching algorithm when applying this idea to the alignment of two ontologies. We have successfully tested the model with the public testcases of the Ontology Alignment Evaluation Initiative 2005.
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Keywords
- Bipartite Graph
- Semantic Similarity
- Resource Description Framework
- Vector Space Model
- Semantic Similarity Measure
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Tous, R., Delgado, J. (2006). A Vector Space Model for Semantic Similarity Calculation and OWL Ontology Alignment. In: Bressan, S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2006. Lecture Notes in Computer Science, vol 4080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11827405_30
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DOI: https://doi.org/10.1007/11827405_30
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