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Reconciling Heterogeneous Knowledge with Ontology Matching

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Agreement Technologies

Part of the book series: Law, Governance and Technology Series ((LGTS,volume 8))

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Abstract

In open, dynamic and distributed systems, it is unrealistic to assume that autonomous agents or peers are committed to a common way of expressing their knowledge, in terms of one or more ontologies modelling the domain of interest. Thus, before any kind of communication or cooperation, agents must reach an agreement on the meaning of the terms they use for structuring information, conceptualizing the world, or representing distinct entities. Over the years several approaches have been proposed for semantic agreement driven by ontology matching in a distributed setting: argumentation-based models, constraint satisfaction methods and probabilistic models. The aim of this chapter is to present a brief overview of the state-of-the-art on these approaches and discuss the main open issues and challenges for future research. We firstly introduce the ontology matching process for semantic agreements and the notion of argumentation frameworks, and then we present scenarios applying such frameworks. Next, we specify the problem of synthesizing different matching methods as a constraint optimization problem and show the benefits of this approach and we present an approach for peers organized in arbitrary networks to reach semantic agreement on their correspondences. Finally, we discuss some open issues and future research directions for semantic agreement based on ontology matching.

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Notes

  1. 1.

    AUML – Agent Unified Modelling Language.

  2. 2.

    Subsequently we assume r to be the equivalence (\(\equiv \)) relation and we also simplify the presentation of correspondence histories by not specifying the correspondence relation and confidence degree for each pair of ontology elements.

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Acknowledgements

In this chapter, we have extended work by Trojahn et al. published in (Trojahn et al. 2011). We also present on-going work for exploiting message passing algorithms for peers/agents organized in arbitrary large-scale networks to reach semantic agreements.

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Authors and Affiliations

  1. INRIA & LIG, Grenoble, France

    Cássia Trojahn

  2. Department of Digital Systems, University of Piraeus, Piraeus, Greece

    George Vouros

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  1. Cássia Trojahn
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  2. George Vouros
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Correspondence to Cássia Trojahn .

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  1. Room DI-241, University Rey Juan, Calle Tulipan s/n, Madrid/Mostoles, 28933, Spain

    Sascha Ossowski

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Trojahn, C., Vouros, G. (2013). Reconciling Heterogeneous Knowledge with Ontology Matching. In: Ossowski, S. (eds) Agreement Technologies. Law, Governance and Technology Series, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5583-3_6

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  • DOI: https://doi.org/10.1007/978-94-007-5583-3_6

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