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Predicting Box Office Receipts of Movies with Pruned Random Forest

  • Zhenyu GuoEmail author
  • Xin Zhang
  • Yuexian HouEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9489)

Abstract

Predicting box office receipts of movies in theatres is a difficult and challenging problem on which many theatre managers cogitated. In this study, we use pruned random forest to predict the box office of the first week in Chinese theatres one month before movies’ theatrical release. In our model, the prediction problem is converted into a classification problem, where the box office receipt of a movie is discretized into eight categories. Experiments on 68 theatres show that the proposed method outperforms other statistical models. In fact, our model can predict the expected revenue range of a movie, it can be used as a powerful decision aid by theatre managers.

Keywords

Chinese theatres Box office Random forest 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyTianjin UniversityTianjinChina

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