Titlebook: Uncertainty Reasoning for the Semantic Web II; International Worksh Fernando Bobillo,Paulo C. G. Costa,Michael Pool Conference proceedings

propose

PR-OWL 2.0 – Bridging the Gap to OWL Semanticsg Multi-Entity Bayesian Network (MEBN) theories. This paper reviews some shortcomings of PR-OWL 1.0 and describes how they are addressed in PR-OWL 2. A method is presented for mapping back and forth between OWL properties and MEBN random variables (RV). The method applies to properties representing both predicates and functions.

斜坡

Assertion Prediction with Ontologies through Evidence Combinationning problem. We show how to exploit the procedure in the problems of determining unknown class- and role-memberships or fillers for datatype properties which may be the basis for many further ABox inductive reasoning algorithms. This work presents also an empirical evaluation of the method on real ontologies.

Engaging

Conference proceedings 2013from numerous submissions. The papers are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy and possibilistic models, inductive reasoning and machine learning, and hybrid approaches.

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Understanding a Probabilistic Description Logic via Connections to First-Order Logic of ProbabilityPL with a specific subjective semantics based on possible worlds. We prove faithfulness of the translation and demonstrate the fundamental nature of some limitations of P-.. Finally, we briefly discuss the implications of the exposed semantic properties of the logic on probabilistic modeling.

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毛細(xì)血管

Finite Fuzzy Description Logics and Crisp Representationsnitially we focus on the finite fuzzy DL ., studying some logical properties, and showing the decidability of the logic by presenting a reasoning preserving reduction to the classical case. Finally, we extend our logic in two directions: by considering non-smooth t-norms and by considering additional DL constructors.

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使混合

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PR-OWL 2.0 – Bridging the Gap to OWL Semanticsx use cases being proposed and explored. As complexity increases in SW applications, so does the need for principled means to represent and reason with uncertainty in SW applications. One candidate representation for uncertainty representation is PR-OWL, which provides OWL constructs for representin

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