TY - GEN
T1 - Interfaces and Human Decision Making for Recommender Systems
AU - Brusilovsky, Peter
AU - De Gemmis, Marco
AU - Felfernig, Alexander
AU - Lops, Pasquale
AU - O'Donovan, John
AU - Semeraro, Giovanni
AU - Willemsen, Martijn C.
PY - 2020/9/22
Y1 - 2020/9/22
N2 - As an interactive intelligent system, recommender systems are developed to give recommendations that match users' preferences. Since the emergence of recommender systems, a large majority of research focuses on objective accuracy criteria and less attention has been paid to how users interact with the system and the efficacy of interface designs from users' perspectives. The field has reached a point where it is ready to look beyond algorithms, into users' interactions, decision making processes, and overall experience. The series of workshops on Interfaces and Human Decision Making for Recommender Systems focuses on the "human side"of recommender systems. The goal of the research stream featured at the workshop is to improve users' overall experience with recommender systems by integrating different theories of human decision making into the construction of recommender systems and exploring better interfaces for recommender systems. In this summary, we introduce 7th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems at RecSys'20, review its history, and discuss most important topics considered at the workshop.
AB - As an interactive intelligent system, recommender systems are developed to give recommendations that match users' preferences. Since the emergence of recommender systems, a large majority of research focuses on objective accuracy criteria and less attention has been paid to how users interact with the system and the efficacy of interface designs from users' perspectives. The field has reached a point where it is ready to look beyond algorithms, into users' interactions, decision making processes, and overall experience. The series of workshops on Interfaces and Human Decision Making for Recommender Systems focuses on the "human side"of recommender systems. The goal of the research stream featured at the workshop is to improve users' overall experience with recommender systems by integrating different theories of human decision making into the construction of recommender systems and exploring better interfaces for recommender systems. In this summary, we introduce 7th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems at RecSys'20, review its history, and discuss most important topics considered at the workshop.
KW - Decision Biases
KW - Evaluation Methods
KW - Human Computer Interaction
KW - Human Decision Making
KW - Recommender Systems
KW - User Interfaces
UR - http://www.scopus.com/inward/record.url?scp=85092725051&partnerID=8YFLogxK
U2 - 10.1145/3383313.3411539
DO - 10.1145/3383313.3411539
M3 - Conference paper
AN - SCOPUS:85092725051
T3 - RecSys 2020 - 14th ACM Conference on Recommender Systems
SP - 613
EP - 618
BT - RecSys 2020 - 14th ACM Conference on Recommender Systems
PB - Association of Computing Machinery
T2 - 14th ACM Conference on Recommender Systems
Y2 - 22 September 2020 through 26 September 2020
ER -