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A Vector Space Model for Semantic Similarity Calculation and OWL Ontology Alignment

  • Rubén Tous
  • Jaime Delgado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)

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.

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Rubén Tous
    • 1
  • Jaime Delgado
    • 1
  1. 1.Distributed Multimedia Applications Group (DMAG)Universitat Politècnica de Catalunya (UPC), Dpt. d’Arquitectura de Computadors, Universitat Pompeu Fabra (UPF), Dpt. de Tecnologia 

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