Publications
カンファレンス (国際) BERT-Based Movie Keyword Search Leveraging User-Generated Movie Rankings and Reviews
Tensho Miyashita (Aoyama Gakuin univ.), Yoshiyuki Shoji (Shizuoka univ.), Sumio Fujita, Martin J. Dürst (Aoyama Gakuin univ.)
2024 International Conference on Big Data and Smart Computing (IEEE BigComp 2024)
2024.2.18
This paper introduces a novel method for movie keyword searches based on user-generated rankings and reviews. We utilize the capabilities of the BERT language model, which has been enriched with task-specific fine-tuning. The model is trained to understand the relationship between keywords and movies using paired user-generated ranking titles and movie reviews. We sourced our data from a renowned Japanese movie review platform. This dataset comprises 10,000 user rankings and 15,000 films. In a binary classification task, our model demonstrated superior performance compared to traditional similaritybased methods. While our approach outperforms traditional similarity methods, further improvements in pooling techniques are necessary.
Paper :
BERT-Based Movie Keyword Search Leveraging User-Generated Movie Rankings and Reviews
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