Trust models for RDF data: Semantics and complexity

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Abstract

Due to the openness and decentralization of the Web, mechanisms to represent and reason about the reliability of RDF data become essential. This paper embarks on a formal analysis of RDF data enriched with trust information by focusing on the characterization of its model-theoretic semantics and on the study of relevant reasoning problems. The impact of trust values on the computational complexity of well-known concepts related to the entailment of RDF graphs is studied. In particular, islands of tractability are identified for classes of acyclic and nearly-acyclic graphs. Moreover, an implementation of the framework and an experimental evaluation on real data are discussed.

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Fionda, V., & Greco, G. (2015). Trust models for RDF data: Semantics and complexity. In Proceedings of the National Conference on Artificial Intelligence (Vol. 1, pp. 95–101). AI Access Foundation. https://doi.org/10.1609/aaai.v29i1.9169

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