AAAI Publications, Twenty-First International Joint Conference on Artificial Intelligence

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Dynamic Selection of Ontological Alignments: A Space Reduction Mechanism
Paul Doran, Valentina Tamma, Terry R. Payne, Ignazio Palmisano

Last modified: 2009-06-26

Abstract


Effective communication in open environments relies on the ability of agents to reach a mutual understanding of the exchanged message by reconciling the vocabulary (ontology) used. Various approaches have considered how mutually acceptable mappings between corresponding concepts in the agents' own ontologies may be determined dynamically through argumentation-based negotiation (such as Meaning-based Argumentation). However, the complexity of this process is high, approaching π2(p)-complete in some cases. As reducing this complexity is non-trivial, we propose the use of ontology modularization as a means of reducing the space over which possible concepts are negotiated. The suitability of different modularization approaches as filtering mechanisms for reducing the negotiation search space is investigated, and a framework that integrates modularization with Meaning-based Argumentation is proposed. We empirically demonstrate that some modularization approaches not only reduce the number of alignments required to reach consensus, but also predict those cases where a service provider is unable to satisfy a request, without the need for negotiation.

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