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Book ChapterDOI

Extending Paraconsistent \mathcal{SROIQ}

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TLDR
It is shown that the modified logic is classically sound and that its embedding into classical \(\mathcal{SROIQ}\) is consequence preserving, and inserting special axioms into a knowledge base allows additional nontrivial conclusions to be drawn, without affecting paraconsistency.
Abstract
The four-valued paraconsistent logic \(\mathcal{SROIQ}4\), originally presented by Ma and Hitzler, is extended to incorporate additional elements of \(\mathcal{SROIQ}\). It is shown that the modified logic is classically sound and that its embedding into classical \(\mathcal{SROIQ}\) is consequence preserving. Furthermore, inserting special axioms into a \(\mathcal{SROIQ}4\) knowledge base allows additional nontrivial conclusions to be drawn, without affecting paraconsistency. It is also shown that the interaction of nominals and cardinality restrictions prevents some \(\mathcal{SROIQ}4\) knowledge bases from having models. For such knowledge bases, the logic remains explosive.

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Citations
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Book ChapterDOI

Scalable OWL 2 reasoning for linked data

TL;DR: The goal of the Scalable OWL 2 Reasoning for Linked data lecture is to introduce scalable reasoning and querying techniques to SemanticWeb researchers as powerful tools to make use of Linked Data and large-scale ontologies.
References
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BookDOI

The Semantic Web: Research and Applications

TL;DR: DODDLE-R, a support environment for user-centered ontology development, consists of two main parts: pre-processing part and quality improvement part, which generates a prototype ontology semi-automatically and supports the refinement of it interactively.
Book ChapterDOI

A Useful Four-Valued Logic

TL;DR: It is argued that a sophisticated question-answering machine that has the capability of making inferences from its data base should employ a certain four-valued logic, the motivating consideration being that minor inconsistencies in its data should not be allowed to lead to irrelevant conclusions.
Proceedings Article

The even more irresistible SROIQ

TL;DR: A rather elegant tableau-based reasoning algorithm that combines the use of automata to keep track of universal value restrictions with the techniques developed for SHOIQ, which has been adopted as the logical basis for the next iteration of OWL, OWL 1.1.
BookDOI

Symbolic and quantitative approaches to reasoning with uncertainty

TL;DR: Symbolic and quantitative approaches to reasoning with uncertainty as mentioned in this paper have been proposed to reason with uncertainty in the context of computer vision applications, such as decision support systems and artificial neural networks.