Why-provenance information for RDF, rules, and negation

DOI10.1007/s10472-013-9396-0zbMath1357.68210OpenAlexW2149965081WikidataQ58198064 ScholiaQ58198064MaRDI QIDQ2248547

Anastasia Analyti, Carlos V. Damásio, Ioannis Pachoulakis, Grigoris Antoniou

Publication date: 26 June 2014

Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10472-013-9396-0

zbMATH Keywords

complexitynegationquery answeringprogram rulesRDF graphswhy-provenance

Mathematics Subject Classification ID

Logic in artificial intelligence (68T27) Knowledge representation (68T30)

Related Items (1)

The Evolution of Context-Aware RDF Knowledge Graphs

Uses Software

• TRIPLE
• Smodels
• SPARQL
• XSB

Cites Work

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• Reconcilable differences
• Extended RDF: computability and complexity issues
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• On database query languages for K-relations
• Complexity results for answer set programming with bounded predicate arities and implications
• Justifications for Logic Programming
• XSB: Extending Prolog with Tabled Logic Programming
• Algebraic Structures for Capturing the Provenance of SPARQL Queries
• Making prolog more expressive
• On negation in Hilog
• The well-founded semantics for general logic programs
• Logical foundations of object-oriented and frame-based languages
• Tabled evaluation with delaying for general logic programs
• The DLV system for knowledge representation and reasoning
• Conflict-Driven Answer Set Enumeration

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