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Establishing agent trust for contradictory evidence by means of fuzzy voting model: An ontology mapping case study
Affiliation:1. University of Central Florida, College of Business Administration, Orlando, FL 32816, United States;2. Alberta School of Business, University of Alberta, Edmonton, AB T6G 2R6, Canada;3. Fuqua School of Business, Duke University, Durham, NC 27708, United States
Abstract:This paper introduces a novel trust assessment formalism for contradicting evidence in the context of multi-agent ontology mapping. Evidence combination using the Dempster rule tend to ignore contradictory evidence and the contemporary approaches for managing these conflicts introduce additional computation complexity i.e. increased response time of the system. On the Semantic Web, ontology mapping systems that need to interact with end users in real time cannot afford prolonged computation. In this work, we have made a step towards the formalisation of eliminating contradicting evidence, to utilise the original Dempster’s combination rule without introducing additional complexity. Our proposed solution incorporates the fuzzy voting model to the Dempster–Shafer theory. Finally, we present a case study where we show how our approach improves the ontology mapping problem.
Keywords:Ontology mapping  Semantic Web  Multi-agent systems  Uncertain reasoning
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