Title :
Multi-model or Single Model? A Study of Movie Box-Office Revenue Prediction
Author :
Guijia He;Soowon Lee
Author_Institution :
Sch. of Comput. Sci. &
Abstract :
Although many studies tried to predict movie revenues in the last decade, the performance and conclusions are conflictive because different data is used. Some studies report that using social data like reviews can obtain the better prediction than using only metadata of movies, but we demonstrate metadata can beat social data in some cases. In this paper, we utilize EM (Expectation Maximization) algorithm to divide movies into several groups, and then for each group we learn one model to predict movie box-office revenue separately. Experimental results show that using multiple models (Multi-model) can obtain more accurate prediction than using a single model (Single-model).
Keywords :
"Motion pictures","Predictive models","Metadata","Partitioning algorithms","Training","Prediction algorithms","Films"
Conference_Titel :
Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM), 2015 IEEE International Conference on
DOI :
10.1109/CIT/IUCC/DASC/PICOM.2015.46