Research on Movie Box Office Prediction Method Based on Blending Model Fusion
Authors: 
Dequan Zheng, Yunjie Sun, Feng YuAuthors Info & Claims
Pages 140 - 146
Abstract
As living standards improve, movies have become an essential commodity and consumer product, playing a pivotal role in people's lives by providing entertainment and enjoyment. Therefore, predicting the movie box office is of great significance. Through studying existing movie box office prediction models, it is found that there are problems such as insufficient selection of box office influencing factors and traditional prediction models. Therefore, this paper mainly selects three models: multiple linear regression, BP neural network, and convolutional neural network, and combines them using Blending model fusion to predict movie box office. Experimental results show that the selected factors and constructed models can improve the prediction effect of box office to a certain extent, which can provide meaningful box office prediction references for movie investors and producers and have certain theoretical and practical significance.
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Published In
February 2024
757 pages
ISBN:9798400709234
DOI:10.1145/3651671
Copyright © 2024 ACM.
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Association for Computing Machinery
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Published: 07 June 2024
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ICMLC 2024
ICMLC 2024: 2024 16th International Conference on Machine Learning and Computing
February 2 - 5, 2024
Shenzhen, China
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