Workshop overview

While individual-focused recommender systems are prevalent, the complexity and dynamics of group scenarios—encompassing factors like interpersonal relationships, group mood, and emotional contagion—pose significant challenges in group recommender systems (GRSys). These group characteristics often remain undefined and fluctuate, complicating their integration into system models. 

GMAP 2024 addresses these issues by gathering researchers across disciplines to explore effective group modelling, adaptation, and personalization strategies. It focuses on the nuanced balance between individual preferences and group needs, emphasizing the development of systems that are explainable, fair, and respectful of privacy concerns to enhance collective decision-making support.