An approach for explaining group recommendations based on negotiation information

VILLAVICENCIO, CHRISTIAN; SILVIA SCHIAFFINO; JORGE ANDRES DIAZ PACE; MONTESERIN, ARIEL

IAES International Journal of Artificial Intelligence

IAES

Año: 2024 vol. 13 p. 162 - 173

2252-8938

Explaining group recommendations has gained importance over the last years.Although the topic of recommendation explanation has received attention in thecontext of single-user recommendations, only a few Group Recommender systems(GRS) currently provide explanations for their group recommendations. However,those GRS that support explanations, provide either explanations being highly relianton the aggregation technique used for generating the recommendation (mostof them trying to tackle shortcomings of the underlying technique), or explanationswith a rich content but requiring users to provide considerable additionaldata. In this article, we present a novel approach for providing explanations ofgroup recommendations, which are generated by a GRS based on multi-agentnegotiation techniques. An evaluation of our approach with a user study in themovies domain has shown promising results. Explanations provided by our GRSsystem helped users during the decision-making process, since they modified thefeedback given to recommended items. This is an improvement with respect tosystems that do not provide explanations for their recommendations.