TY - GEN
T1 - Recommender systems with personality
AU - Azaria, Amos
AU - Hong, Jason
N1 - Publisher Copyright:
© 2016 Copyright held by the owner/author(s).
PY - 2016/9/7
Y1 - 2016/9/7
N2 - We believe that in the future, the most common form of recommender systems will be present in a personal assistant. We claim that such an intelligent agent must be personal, i.e., know its user's preferences and recommend relevant content, a dynamic learner, instructable, supportive and affable. We describe the current state of the art and the challenges which should be addressed in each of these agent properties and provide examples of how we expect future personal agents to convey these properties.
AB - We believe that in the future, the most common form of recommender systems will be present in a personal assistant. We claim that such an intelligent agent must be personal, i.e., know its user's preferences and recommend relevant content, a dynamic learner, instructable, supportive and affable. We describe the current state of the art and the challenges which should be addressed in each of these agent properties and provide examples of how we expect future personal agents to convey these properties.
UR - https://www.scopus.com/pages/publications/84991207711
U2 - 10.1145/2959100.2959138
DO - 10.1145/2959100.2959138
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AN - SCOPUS:84991207711
T3 - RecSys 2016 - Proceedings of the 10th ACM Conference on Recommender Systems
SP - 207
EP - 210
BT - RecSys 2016 - Proceedings of the 10th ACM Conference on Recommender Systems
T2 - 10th ACM Conference on Recommender Systems, RecSys 2016
Y2 - 15 September 2016 through 19 September 2016
ER -