Détails Publication
ARTICLE

Categorizing Approaches to Justify Recommendations

  • Proceeding of Machine Intelligence Research Group, University of Lagos V. Odumuyiwa et. al. (Eds.): MIRG-ICAIR : 33-38
Discipline : Informatique et sciences de l'information
Auteur(s) :
Auteur(s) tagués : KABORE Kiswendsida Kisito
Renseignée par : KABORE Kiswendsida Kisito

Résumé

Recommendation justification enables users to understand the reasons and motivation behind
the recommendation of an item in a recommender system. It makes the recommendation model
much more transparent, and improves user satisfaction. It is because of the important role
assigned to the justification of recommendations that the present work aims to identify the
approaches and methods for justifying recommendations that exist in the literature. The state
of the art has enabled us to categorize the different approaches to recommendation
justification. There are two approaches to recommendation justification: the linked model and
the post-hoc models. The data used for justification are external or internal to the items.

Mots-clés

Recommender systems, Justification of recommendation, Model-based justification, Post-hoc justification

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