State of art and emerging trends on group recommender system: a comprehensive review

A group recommender system (GRS) generates suggestions for a group of individuals, considering not only each person's preferences but also factors such as social dynamics and behavior to deliver recommendations that balance personal taste and social factors. In this study, 225 papers have been analyzed from different journals and conference papers, covering a variety of literature works on group recommendation systems. The articles in the literature used for the review were published between 2010 and 2023. This overview of the literature focuses on several methods for creating group recommender systems. This review starts by providing an overview of group recommender systems, including the challenges and essential elements for their development. It then examines the existing literature on collaborative, content-based, and knowledge-based group recommendation techniques. Beyond traditional approaches, this study identifies a notable research gap in the integration of audio, image, and video recommendation systems within the group recommendation paradigm. It then discusses the research gaps found in the existing papers. The review also discusses various aggregation techniques and evaluation metrics used to evaluate these techniques. The review concludes by discussing the limitations and potential future directions for group recommendation research. This review aims to give a thorough understanding of the current status of group recommendations and to pinpoint potential areas for future study.