Extracting Bounded-Level Modules from Deductive RDF Triplestores

Marie-Christine Rousset, Federico Ulliana

AAAI 2015 pp. 268-274

doi:10.1609/AAAI.V29I1.9176 /aaai/2015/rousset2015aaai-extracting/

Abstract

We present a novel semantics for extracting bounded-level modules from RDF ontologies and databases augmented with safe inference rules, a 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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Cite

Text

Rousset and Ulliana. "Extracting Bounded-Level Modules from Deductive RDF Triplestores." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9176

Markdown

[Rousset and Ulliana. "Extracting Bounded-Level Modules from Deductive RDF Triplestores." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/rousset2015aaai-extracting/) doi:10.1609/AAAI.V29I1.9176

BibTeX

@inproceedings{rousset2015aaai-extracting,
  title     = {{Extracting Bounded-Level Modules from Deductive RDF Triplestores}},
  author    = {Rousset, Marie-Christine and Ulliana, Federico},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2015},
  pages     = {268-274},
  doi       = {10.1609/AAAI.V29I1.9176},
  url       = {https://mlanthology.org/aaai/2015/rousset2015aaai-extracting/}
}