TY - GEN
T1 - First workshop on the impact of recommender systems at ACM REcSys 2019
AU - Shalom, Oren Sar
AU - Jannach, Dietmar
AU - Guy, Ido
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/9/10
Y1 - 2019/9/10
N2 - Research in the area of recommender systems is largely focused on the value such a system creates for the users, by helping them fnding items they are interested in. This is usually done by learning to rank the recommendable items based on their assumed relevance for each user. The implicit underlying goal often is that this personalization positively afects users in diferent positive ways, e.g., by making their search and decision processes easier or by helping them discover new things [3].
AB - Research in the area of recommender systems is largely focused on the value such a system creates for the users, by helping them fnding items they are interested in. This is usually done by learning to rank the recommendable items based on their assumed relevance for each user. The implicit underlying goal often is that this personalization positively afects users in diferent positive ways, e.g., by making their search and decision processes easier or by helping them discover new things [3].
KW - Evaluation
KW - Impact of Recommender Systems
UR - http://www.scopus.com/inward/record.url?scp=85073350086&partnerID=8YFLogxK
U2 - 10.1145/3298689.3347060
DO - 10.1145/3298689.3347060
M3 - Conference contribution
AN - SCOPUS:85073350086
T3 - RecSys 2019 - 13th ACM Conference on Recommender Systems
SP - 556
EP - 557
BT - RecSys 2019 - 13th ACM Conference on Recommender Systems
PB - Association for Computing Machinery, Inc
T2 - 13th ACM Conference on Recommender Systems, RecSys 2019
Y2 - 16 September 2019 through 20 September 2019
ER -