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Asymmetric and Context-Dependent Semantic Similarity among Ontology Instances

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Journal on Data Semantics X

Part of the book series: Lecture Notes in Computer Science ((JODS,volume 4900))

Abstract

In this paper we propose an asymmetric semantic similarity among instances within an ontology. We aim to define a measurement of semantic similarity that exploit as much as possible the knowledge stored in the ontology taking into account different hints hidden in the ontology definition. The proposed similarity measurement considers different existing similarities, which we have combined and extended. Moreover, the similarity assessment is explicitly parameterised according to the criteria induced by the context. The parameterisation aims to assist the user in the decision making pertaining to similarity evaluation, as the criteria can be refined according to user needs. Experiments and an evaluation of the similarity assessment are presented showing the efficiency of the method.

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Authors and Affiliations

  1. CNR-IMATI, Via De Marini, 6, Torre di Francia, 16149, Genova, Italy

    Riccardo Albertoni & Monica De Martino

Authors
  1. Riccardo Albertoni
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  2. Monica De Martino
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Stefano Spaccapietra

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Albertoni, R., De Martino, M. (2008). Asymmetric and Context-Dependent Semantic Similarity among Ontology Instances. In: Spaccapietra, S. (eds) Journal on Data Semantics X. Lecture Notes in Computer Science, vol 4900. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77688-8_1

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  • DOI: https://doi.org/10.1007/978-3-540-77688-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77687-1

  • Online ISBN: 978-3-540-77688-8

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