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Conference Papers Year : 2017

Crafting ontology alignments from scratch through agent communication

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Abstract

Agents may use different ontologies for representing knowledge and take advantage of alignments between ontologies in order to communicate. Such alignments may be provided by dedicated algorithms, but their accuracy is far from satisfying. We already explored operators allowing agents to repair such alignments while using them for communicating. The question remained of the capability of agents to craft alignments from scratch in the same way. Here we explore the use of expanding repair operators for that purpose. When starting from empty alignments, agents fails to create them as they have nothing to repair. Hence, we introduce the capability for agents to risk adding new correspondences when no existing one is useful. We compare and discuss the results provided by this modality and show that, due to this generative capability, agents reach better results than without it in terms of the accuracy of their alignments. When starting with empty alignments, alignments reach the same quality level as when starting with random alignments, thus providing a reliable way for agents to build alignment from scratch through communication.
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Dates and versions

hal-01661140 , version 1 (21-12-2017)

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Jérôme Euzenat. Crafting ontology alignments from scratch through agent communication. PRIMA 2017: Principles and Practice of Multi-Agent Systems, Oct 2017, Nice, France. pp.245-262, ⟨10.1007/978-3-319-69131-2_15⟩. ⟨hal-01661140⟩
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