Web of Data Evolution by Exploiting Agent Based-Argumentation

Abstract : Sharing knowledge and data coming from different sources is one of the biggest advantage of linked data. Keeping this knowledge graph up to date may take in account both ontology vocabularies and data since they should be consistent. Our general problem is to deal with web of data evolution in particular: We aim at assisting user in a such complex process. In this research work, we propose an agent based-argumentation framework to help user linked data changes. We assign for each agent a goal to acheive as process step. We rely upon communication-argumentation potential of the agent to harmonise changes with consistency.
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Fatma Chamekh, Danielle Boulanger, Guilaine Talens. Web of Data Evolution by Exploiting Agent Based-Argumentation. 3rd IFIP International Workshop on Artificial Intelligence for Knowledge Management (AI4KM), Jul 2015, Buenos Aires, Argentina. pp.32-50. ⟨hal-01626994⟩

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