TY - GEN
T1 - "i like to explore sometimes"
T2 - 9th ACM Conference on Recommender Systems, RecSys 2015
AU - Kapoor, Komal
AU - Kumar, Vikas
AU - Terveen, Loren
AU - Konstan, Joseph A.
AU - Schrater, Paul
PY - 2015/9/16
Y1 - 2015/9/16
N2 - Studies have shown that the recommendation of unseen, novel or serendipitous items is crucial for a satisfying and engaging user experience. As a result, recent developments in recommendation research have increasingly focused towards introducing novelty in user recommendation lists. While, existing solutions aim to find the right balance between the similarity and novelty of the recommended items, they largely ignore the user needs for novelty. In this paper, we show that there are large individual and temporal differences in the users' novelty preferences. We develop a regression model to predict these dynamic novelty preferences of users using features derived from their past interactions. Finally, we describe an adaptive recommender, adaNov-R, that adapts to the user needs for novel items and show that the model achieves better recommendation performance on a metric that considers both novel and familiar items.
AB - Studies have shown that the recommendation of unseen, novel or serendipitous items is crucial for a satisfying and engaging user experience. As a result, recent developments in recommendation research have increasingly focused towards introducing novelty in user recommendation lists. While, existing solutions aim to find the right balance between the similarity and novelty of the recommended items, they largely ignore the user needs for novelty. In this paper, we show that there are large individual and temporal differences in the users' novelty preferences. We develop a regression model to predict these dynamic novelty preferences of users using features derived from their past interactions. Finally, we describe an adaptive recommender, adaNov-R, that adapts to the user needs for novel items and show that the model achieves better recommendation performance on a metric that considers both novel and familiar items.
KW - Diversity
KW - Dynamic user preferences
KW - Novelty
KW - Recommendation systems
UR - http://www.scopus.com/inward/record.url?scp=84962856575&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962856575&partnerID=8YFLogxK
U2 - 10.1145/2792838.2800172
DO - 10.1145/2792838.2800172
M3 - Conference contribution
AN - SCOPUS:84962856575
T3 - RecSys 2015 - Proceedings of the 9th ACM Conference on Recommender Systems
SP - 19
EP - 26
BT - RecSys 2015 - Proceedings of the 9th ACM Conference on Recommender Systems
PB - Association for Computing Machinery, Inc
Y2 - 16 September 2015 through 20 September 2015
ER -