ML Anthology

A Model for Accountable Ordinal Sorting

Khaled Belahcène, Christophe Labreuche, Nicolas Maudet, Vincent Mousseau, Wassila Ouerdane
IJCAI 2017 pp. 814-820
doi:10.24963/IJCAI.2017/113 /ijcai/2017/belahcene2017ijcai-model/

Abstract

We address the problem of multicriteria ordinalsorting through the lens of accountability, i.e. theability of a human decision-maker to own a recommendationmade by the system. We put forward anumber of model features that would favor the capabilityto support the recommendation with a convincingexplanation. To account for that, we designa recommender system implementing and formalizingsuch features. This system outputs explanationsdefined under the form of specific argumentschemes tailored to represent the specific rules ofthe model. At the end, we discuss possible andpromising argumentative perspectives.

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Text

Belahcène et al. "A Model for Accountable Ordinal Sorting." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/113

Markdown

[Belahcène et al. "A Model for Accountable Ordinal Sorting." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/belahcene2017ijcai-model/) doi:10.24963/IJCAI.2017/113

BibTeX

@inproceedings{belahcene2017ijcai-model,
  title     = {{A Model for Accountable Ordinal Sorting}},
  author    = {Belahcène, Khaled and Labreuche, Christophe and Maudet, Nicolas and Mousseau, Vincent and Ouerdane, Wassila},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {814-820},
  doi       = {10.24963/IJCAI.2017/113},
  url       = {https://mlanthology.org/ijcai/2017/belahcene2017ijcai-model/}
}