Authors:
Silvia Rossi
and
Francesco Cervone
Affiliation:
Universita’ degli Studi di Napoli “Federico II”, Italy
Keyword(s):
Social Choice, Group Recommendation, Big-Five, Group Decision Making.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Group Decision Making
Abstract:
Recommendations to a group of users can be provided by the aggregation of individual users’ recommendations using social choice functions. Standard aggregation techniques do not consider the possibility of evaluating social interactions, roles, and influences among group’s members, as well as their personalities, which are, indeed, crucial factors in the group’s decision-making process. Instead of defining a specific social choice function to take into account such features, the proposed solution relies on the definition of a utility function, for each agent, that takes into account other group members’ preferences. Such function models the level of a user’s altruistic behavior starting from his/her agreeableness personality trait. Once such utility values are evaluated, the goal is to recommend items that maximize the social welfare. Performance is evaluated with a pilot user study and compared with respect to Least Misery. Results showed that while for small groups LM performs slig
htly better, in the other cases the two methods are comparable.
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