Name
Abstract | ||
|---|---|---|
We address the problem of multicriteria ordinal sorting through the lens of accountability, i.e. the ability of a human decision-maker to own a recommendation made by the system. We put forward a number of model features that would favor the capability to support the recommendation with a convincing explanation. To account for that, we design a recommender system implementing and formalizing such features. This system outputs explanations under the form of specific argument schemes tailored to represent the specific rules of the model. At the end, we discuss possible and promising argumentative perspectives. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.24963/ijcai.2017/113 | IJCAI |
Field | DocType | Citations |
Recommender system,Preference elicitation,Argumentative,Ordinal number,Computer science,Accountability,Sorting,Through-the-lens metering,Artificial intelligence,Machine learning | Conference | 1 |
PageRank | References | Authors |
0.35 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khaled Belahcene | 1 | 1 | 1.70 |
| Christophe Labreuche | 2 | 709 | 65.78 |
| Nicolas Maudet | 3 | 33 | 4.46 |
| Vincent Mousseau | 4 | 808 | 50.52 |
| Wassila Ouerdane | 5 | 20 | 5.53 |