Group Recommendations Based on Hesitant Fuzzy Sets
作者： Jorge Castro , Manuel J. Barranco , Rosa M. Rodríguez , Luis Martínez
DOI: 10.1002/INT.21922
关键词:
摘要: Group recommender systems (GRSs) recommend items that are used by groups of people because certain activities, such as listening to music, watching a movie, dining in restaurant, etc., social events performed sharing their tastes, and choices affect all them. GRSs help making overloaded search spaces according group members preferences. A common GRS scheme aggregates users preferences generate preference profile. However, the aggregation process may imply loss information, negatively affecting different properties diversity recommendations, which is an important quality factor recommendations targeted formed with individual possibly conflicting To avoid manage information caused aggregation, this paper proposes keep using hesitant fuzzy sets (HFSs) interpreting like hesitation about will be recommendation process. evaluate performance rank HFS proposal, case study carried out.
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