Explainability Group recommendation Recommender systems

PRISM: From Individual Preferences to Group Consensus through Conversational AI-Mediated and Visual Explanations

In group accommodation booking, delegating coordination to messaging apps and informal voting often leads to opaque preference trade-offs and social influence, which results in decisions that reflect dominance or conformity rather than genuine consensus. Conversational elicitation coupled with visual preference alignment can enable groups to surface, compare, and negotiate constraints transparently by separating private preference …

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Group recommendation

Enabling Reproducibility in Group Recommender Systems

Group recommender systems produce suggestions in contexts in which more than one person is involved in the recommendation process. They present additional tasks w.r.t. those for single users, such as the identification of the groups, or their modeling. While this clearly amplifies the possible reproducibility issues, to date, no framework to benchmark group recommender systems …

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