TY - GEN
T1 - GMAP 2023: 2nd Workshop on Group Modeling, Adaptation and Personalization
AU - Barile, F.
AU - Delic, A.
AU - Peška, L.
AU - Saccardi, I.
AU - Ulusoy, O.
AU - Vinella, F.
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/6/26
Y1 - 2023/6/26
N2 - Although most existing recommender systems support single users, there are many scenarios where these systems target the needs of groups. Traits such as group mood, emotional contagion, and interpersonal relationships are often ill-defined characteristics, tend to mutate over time, and are usually missing from the systems’ modeling, even though they play an indispensable part in group modeling. Furthermore, producing timely and accurate recommendations for groups that are explainable, fair, and privacy-protecting is a notoriously tricky challenge since group members may have divergent views and needs. The second GMAP workshop aims at bringing together a community of researchers focused on group modeling, adaptation, and personalization. The objective is to explore the challenges and opportunities of developing effective methods and tools to support group decision-making. The workshop, we brought together researchers from several disciplines, including Psychology, Computer Science, and Organizational Behavior, to discuss their latest research and ideas on this topic. It also provided opportunities for participants to share their research and experiences and to collaborate and network with other researchers in this field. The long-term goal is to foster a vibrant and inclusive community of researchers committed to advancing our understanding of group modeling, adaptation, and personalization by bringing together experts from different disciplines and perspectives. Throughout this workshop, we aim to identify critical challenges and opportunities in this area and develop a shared research agenda to guide future work.
AB - Although most existing recommender systems support single users, there are many scenarios where these systems target the needs of groups. Traits such as group mood, emotional contagion, and interpersonal relationships are often ill-defined characteristics, tend to mutate over time, and are usually missing from the systems’ modeling, even though they play an indispensable part in group modeling. Furthermore, producing timely and accurate recommendations for groups that are explainable, fair, and privacy-protecting is a notoriously tricky challenge since group members may have divergent views and needs. The second GMAP workshop aims at bringing together a community of researchers focused on group modeling, adaptation, and personalization. The objective is to explore the challenges and opportunities of developing effective methods and tools to support group decision-making. The workshop, we brought together researchers from several disciplines, including Psychology, Computer Science, and Organizational Behavior, to discuss their latest research and ideas on this topic. It also provided opportunities for participants to share their research and experiences and to collaborate and network with other researchers in this field. The long-term goal is to foster a vibrant and inclusive community of researchers committed to advancing our understanding of group modeling, adaptation, and personalization by bringing together experts from different disciplines and perspectives. Throughout this workshop, we aim to identify critical challenges and opportunities in this area and develop a shared research agenda to guide future work.
KW - Explainability
KW - Group Formation
KW - Group Psychology
KW - Group Recommender Systems
KW - Privacy
UR - http://www.scopus.com/inward/record.url?scp=85163726830&partnerID=8YFLogxK
U2 - 10.1145/3563359.3595628
DO - 10.1145/3563359.3595628
M3 - Conference contribution
SN - 978-1-4503-9891-6
T3 - UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
SP - 249
EP - 252
BT - UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
PB - Association for Computing Machinery
ER -