Abstract
While most recommender systems cater to individual users' needs, there are numerous situations where these systems are needed to meet groups' demands. These systems are broadly labelled as Group Recommender Systems (GRSys). Traits like interpersonal relationships, group mood, and emotional contagion are essential to fulfilling the group's needs. However, the group's characteristics are frequently ill-defined and dynamic and are typically absent from systems modeling. Moreover, GRSys must maneuver between the needs of the group and the individuals when opinions differ and can contradict each other. The third edition of GMAP proposes consolidating a community of scholars interested in group modeling, adaptation, and personalization. Through the workshop, researchers continue their examination of the difficulties and possibilities of creating efficient procedures and instruments to facilitate collective decision-making. GMAP 2024 offered this unique opportunity to gather scholars from different fields to enrich discussions over GRSys' research. The workshop also allowed attendees to strengthen their networks and establish new connections conducive to cutting-edge collaborative research.
Original language | English |
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Title of host publication | UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization |
Publisher | Association for Computing Machinery (ACM) |
Pages | 316-318 |
Number of pages | 3 |
ISBN (Electronic) | 9798400704666 |
DOIs | |
Publication status | Published - 27 Jun 2024 |
Event | 32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024 - Cagliari, Sardinia, Italy Duration: 1 Jul 2024 → 4 Jul 2024 https://www.um.org/umap2024/ |
Conference
Conference | 32nd ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2024 |
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Abbreviated title | UMAP 2024 |
Country/Territory | Italy |
City | Cagliari, Sardinia |
Period | 1/07/24 → 4/07/24 |
Internet address |
Keywords
- Explainability
- Group Formation
- Group Psychology
- Group Recommender Systems