| SHU Zhan（舒展）,DUAN Yong.[J].高技术通讯(英文),2023,29(1):98~104 |
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| Prediction of film ratings based on domain adaptive transfer learning |
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| DOI：10. 3772/ j. issn. 1006-6748. 2023. 01. 011 |
| 中文关键词: |
| 英文关键词: prediction of film rating, domain adaptive, transfer component analysis (TCA), correlation alignment (CORAL), stacking |
| 基金项目: |
| Author Name | Affiliation | | SHU Zhan（舒展） | (School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, P.R.China) | | DUAN Yong | (School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, P.R.China) |
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| 中文摘要: |
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| 英文摘要: |
| This paper examines the prediction of film ratings. Firstly, in the data feature engineering, feature construction is performed based on the original features of the film dataset. Secondly, the clustering algorithm is utilized to remove singular film samples, and feature selections are carried out. When solving the problem that film samples of the target domain are unlabelled, it is impossible to train a model and address the inconsistency in the feature dimension for film samples from the source domain. Therefore, the domain adaptive transfer learning model combined with dimensionality reduction algorithms is adopted in this paper. At the same time, in order to reduce the prediction error of models, the stacking ensemble learning model for regression is also used. Finally, through comparative experiments, the effectiveness of the proposed method is verified, which proves to be better predicting film ratings in the target domain. |
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