Détails Publication
Comparative study of justification Methods in recommender systems: Example of information access Assistance service (IAAS),
Discipline: Informatique et sciences de l'information
Auteur(s): Kyelem Yacouba, Kabore Kiswendsida Kisito, Ouedraogo Tounwendyam Frédéric, Sèdes Florence
Auteur(s) tagués: KABORE Kiswendsida Kisito
Renseignée par : KABORE Kiswendsida Kisito
Résumé

Justification of recommendations increases trust between users and the system but also
generates more relevant recommendations than recommendation systems that do not
incorporate it. That is why, we conducted a justification study of the recommendation for IAAS.
Our comparative study shows that IAAS, which currently does not offer the opportunity to justify
recommendations, needs to be improved. From the analysis of justification methods studied in
this work, it appears that none of these methods can be used effectively in IAAS. That is why, we
proposed a new IAAS architecture that deals separately with item classification and the
extraction of the justification has added the item during recommendation generation. The item
selection method remains unchanged as we plan to implement a new strategy to filter user’s
reviews should now be extended to four elements: the documentary unit, the group of users, the
justification and the weight. Opinion A=(UD,G,J,a). Where UD represents the documentary
unit, G the user group, J is the justification and a is the weight of the recommendation.

Mots-clés

IAAS, Justification in Recommender Systems, users reviews, weight of reviews.

935
Enseignants
7844
Publications
49
Laboratoires
101
Projets