Movie recommender system for profit maximization (short LBP)

Amos Azaria, Avinatan Hassidim, Sarit Kraus, Adi Eshkol, Ofer Weintraub, Irit Netanely

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationLate-Breaking Developments in the Field of Artificial Intelligence - Papers Presented at the 27th AAAI Conference on Artificial Intelligence, Technical Report
PublisherAI Access Foundation
Pages5-7
Number of pages3
ISBN (Print)9781577356288
StatePublished - 2013
Externally publishedYes
Event27th AAAI Conference on Artificial Intelligence, AAAI 2013 - Bellevue, WA, United States
Duration: 14 Jul 201318 Jul 2013

Publication series

NameAAAI Workshop - Technical Report
VolumeWS-13-17

Conference

Conference27th AAAI Conference on Artificial Intelligence, AAAI 2013
Country/TerritoryUnited States
CityBellevue, WA
Period14/07/1318/07/13

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