Abstract
With the rapid development of the movie industry, it is vital to evaluate and predict a movie’s quality. In this paper, a movie score prediction model is proposed based on the movie plots. Movie data was processed with the word2vec method, and the linear regression model and back propagation neural network algorithm were employed to establish the movie score prediction model. The high-quality classic movie plots of high-scoring movies summed up by big data contributed to a high synthesis of the wonderful content of the film. Experimental results show that it is effective in terms of movie evaluation and prediction, and helpful in understanding people’s preferences for movie plots.
H. Xie and H. Wang—These authors contributed equally to this work and should be considered co-first authors.
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Acknowledgments
This work was supported by Natural Science Foundation of Jilin Provincial Science and Technology Department (20180101016JC); Science and Technology Development Plan of Jilin Province (20180101054JC).
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Xie, H., Wang, H., Zhao, C., Wang, Z. (2019). Movie Score Prediction Model Based on Movie Plots. In: Mao, R., Wang, H., Xie, X., Lu, Z. (eds) Data Science. ICPCSEE 2019. Communications in Computer and Information Science, vol 1059. Springer, Singapore. https://doi.org/10.1007/978-981-15-0121-0_49
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DOI: https://doi.org/10.1007/978-981-15-0121-0_49
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