Affiliation:
1. CentraleSupélec
2. Thales Reserach & Technology
3. UPMC Univ. Paris 6
4. CentraleSuepélec
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.
Publisher
International Joint Conferences on Artificial Intelligence Organization
Cited by
1 articles.
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