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AAAI 2015

Extracting Bounded-Level Modules from Deductive RDF Triplestores

Conference Paper Papers Artificial Intelligence

Abstract

We present a novel semantics for extracting bounded-level modules from RDF ontologies and databases augmented with safe inference rules, à la Datalog. Dealing with a recursive rule language poses challenging issues for defining the module semantics, and also makes module extraction algorithmically unsolvable in some cases. Our results include a set of module extraction algorithms compliant with the novel semantics. Experimental results show that the resulting framework is effective in extracting expressive modules from RDF datasets with formal guarantees, whilst controlling their succinctness.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
442868596174504910
v2026.09.13