Learning argumentative recommenders - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Learning argumentative recommenders

Résumé

Recommender systems aim at recommending some item as most appropriate for the user. This article introduces a new way of measuring appropriateness for the user: an item is among the most appropriate ones if it is among the preferred items of the user when considering all arguments in favor or against all possible items. I describe precisely this goal and describe what a recommender system aiming for that goal could look like, called an Argumentative Recommender. I also provide a way of measuring whether a recommender system has achieved the goal, which can be used to compare such recommender systems, and briefly outline a way of building such a system.
Fichier principal
Vignette du fichier
da2pl2018-abstract-09-1.pdf (310.61 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-04176648 , version 1 (03-08-2023)

Licence

Identifiants

  • HAL Id : hal-04176648 , version 1

Citer

Olivier Cailloux. Learning argumentative recommenders. DA2PL'2018: From Multiple Criteria Decision Aid to Preference Learning, Krzysztof Dembczyński; Milosz Kadziński, Nov 2018, Poznan, Poland. ⟨hal-04176648⟩
27 Consultations
5 Téléchargements

Partager

Gmail Mastodon Facebook X LinkedIn More