MBase: representing knowledge and context for the intergration of mathematical software systems
Journal of Symbolic Computation - Calculemus-99: integrating computation and deduction
Reconstruction Proofs at the Assertion Level
CADE-12 Proceedings of the 12th International Conference on Automated Deduction
Explaining reasoning in description logics
Explaining reasoning in description logics
Natural Language Engineering
Explaining answers from the Semantic Web: the Inference Web approach
Web Semantics: Science, Services and Agents on the World Wide Web
Bringing Semantics to Web Services with OWL-S
World Wide Web
What Makes You Think That? The Semantic Web's Proof Layer
IEEE Intelligent Systems
Proof explanation for a nonmonotonic Semantic Web rules language
Data & Knowledge Engineering
Proceedings of the 17th international conference on World Wide Web
An initial investigation on evaluating semantic web instance data
Proceedings of the 17th international conference on World Wide Web
IAAI'07 Proceedings of the 19th national conference on Innovative applications of artificial intelligence - Volume 2
Querying for provenance, trust, uncertainty and other meta knowledge in RDF
Web Semantics: Science, Services and Agents on the World Wide Web
Adaptive systems in the era of the semantic and social web, a survey
User Modeling and User-Adapted Interaction
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The Semantic Web is being designed to enable automated reasoners to be used as core components in a wide variety of Web applications and services. In order for a client to accept and trust a result produced by perhaps an unfamiliar Web service, the result needs to be accompanied by a justification that is understandable and usable by the client. In this paper, we describe the proof markup language (PML), an interlingua representation for justifications of results produced by Semantic Web services. We also introduce our Inference Web infrastructure that uses PML as the foundation for providing explanations of Web services to end users. We additionally show how PML is critical for and provides the foundation for hybrid reasoning where results are produced cooperatively by multiple reasoners. Our contributions in this paper focus on technological foundations for capturing formal representations of term meaning and justification descriptions thereby facilitating trust and reuse of answers from web agents.