On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts

Éric Grégoire, Yacine Izza, Jean-Marie Lagniez

AAAI 2016 pp. 3404-3410

doi:10.1609/AAAI.V30I1.10431 /aaai/2016/gregoire2016aaai-extraction/

Abstract

The efficient extraction of one maximal information subset that does not conflict with multiple contxts or additional information sources is a key basic issue in many A.I. domains, especially when these contexts or sources can be mutually conflicting. In this paper, this question is addressed from a computational point of view in clausal Boolean logic. A new approach is introduced that experimentally outperforms the currently most efficient technique.

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Cite

Text

Grégoire et al. "On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.10431

Markdown

[Grégoire et al. "On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/gregoire2016aaai-extraction/) doi:10.1609/AAAI.V30I1.10431

BibTeX

@inproceedings{gregoire2016aaai-extraction,
  title     = {{On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts}},
  author    = {Grégoire, Éric and Izza, Yacine and Lagniez, Jean-Marie},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {3404-3410},
  doi       = {10.1609/AAAI.V30I1.10431},
  url       = {https://mlanthology.org/aaai/2016/gregoire2016aaai-extraction/}
}