TY - GEN
T1 - Movie recommender system for profit maximization (short LBP)
AU - Azaria, Amos
AU - Hassidim, Avinatan
AU - Kraus, Sarit
AU - Eshkol, Adi
AU - Weintraub, Ofer
AU - Netanely, Irit
PY - 2013
Y1 - 2013
N2 - In this paper we provide an algorithm for utility maximization of a movie supplier service, in two different settings, one with prices and the other without. This algorithm is provided along with an extensive experiment demonstrating its performance. We also uncover a phenomenon where movie consumers prefer watching and even paying for movies that they have already seen in the past than movies that are new to them.
AB - In this paper we provide an algorithm for utility maximization of a movie supplier service, in two different settings, one with prices and the other without. This algorithm is provided along with an extensive experiment demonstrating its performance. We also uncover a phenomenon where movie consumers prefer watching and even paying for movies that they have already seen in the past than movies that are new to them.
UR - http://www.scopus.com/inward/record.url?scp=84898866205&partnerID=8YFLogxK
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AN - SCOPUS:84898866205
SN - 9781577356288
T3 - AAAI Workshop - Technical Report
SP - 5
EP - 7
BT - Late-Breaking Developments in the Field of Artificial Intelligence - Papers Presented at the 27th AAAI Conference on Artificial Intelligence, Technical Report
PB - AI Access Foundation
T2 - 27th AAAI Conference on Artificial Intelligence, AAAI 2013
Y2 - 14 July 2013 through 18 July 2013
ER -