Abstract
In the distributed ontology alignment construction problem, two agents agree upon a meaningful subset of correspondences that map between their respective ontologies. However, an agent may be tempted to manipulate the negotiation in favour of a preferred alignment by misrepresenting the weight or confidence of the exchanged correspondences. Therefore such an agreement can only be meaningful if the agents can be incentivised to be honest when revealing information. We examine this problem and model it as a novel mechanism design problem on an edge-weighted bipartite graph, where each side of the graph represents each agent’s private entities, and where each agent maintains a private set of valuations associated with its candidate correspondences. The objective is to find a matching (i.e. injective or one-to-one correspondences) that maximises the agents’ social welfare. We study implementations in dominant strategies, and show that they should be solved optimally if truthful mechanisms are required. A decentralised version of the greedy allocation algorithm is then studied with a first-price payment rule, proving tight bounds on the Price of Anarchy and Stability.
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Notes
- 1.
For a comprehensive overview of the different approaches, we refer the reader to the Ontology Alignment Evaluation Initiative - http://oaei.ontologymatching.org.
- 2.
A classic example of terminological difference exists with the term “football”, which has a different meaning depending on whether the reader is from the US or the UK.
- 3.
We follow the standard practice of restricting ourselves to correspondences between named concepts within the respective ontologies [10], and omit the discussion of the property relations between entities within each ontology.
- 4.
The notion of a bid profile across a set of agents that omits the bid of agent i, represented as \(b_{-i}\) originates from the definition of the Vickrey Clarke Groves (VCG) mechanism [25], used extensively in mechanism design.
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Zhi, N., Payne, T.R., Krysta, P., Li, M. (2019). Truthful Mechanisms for Multi Agent Self-interested Correspondence Selection. In: Ghidini, C., et al. The Semantic Web – ISWC 2019. ISWC 2019. Lecture Notes in Computer Science(), vol 11778. Springer, Cham. https://doi.org/10.1007/978-3-030-30793-6_42
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DOI: https://doi.org/10.1007/978-3-030-30793-6_42
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