RATING RATE PREDICTION USING BEHAVIOUR SEQUENCE TRANSFORMER FOR MOVIE RATING IN OTT (OVER THE TOP)
Alt Text: Rating Rate Prediction Using Behaviour Sequence Transformer for Movie Rating in OTT
Title: Rating Rate Prediction Using Behaviour Sequence Transformer for Movie Rating in OTT
Caption: Utilizing Behaviour Sequence Transformer for accurate rating predictions in online streaming platforms.
Description: This study presents a novel approach for predicting user ratings in OTT platforms using Behaviour Sequence Transformer (BST), capturing temporal dependencies in user interactions for enhanced recommendation accuracy. The proposed method demonstrates improved predictive robustness on real-world datasets.
Keywords: Movie Rating Prediction, Behaviour Sequence Transformer, OTT Platforms, Recommendation Systems, Machine Learning
International Journal of Engineering and Techniques – Volume 10 Issue 3, June 2024
Gandikota Kethana1, Machavaram Manjudevika2
1UG Student, Department of Computer Science & Engineering, Geethanjali Institute of Science and Technology, Gangavaram, Andhra Pradesh, India.
2UG Student, Department of Computer Science & Engineering, Geethanjali Institute of Science and Technology, Gangavaram, Andhra Pradesh, India.
Abstract
The proliferation of online platforms has led to an abundance of user-generated ratings and reviews across entertainment, e-commerce, and hospitality domains. Predicting user ratings accurately is essential for personalized recommendation systems and business intelligence applications. This research introduces a Behaviour Sequence Transformer (BST) model designed to capture temporal dependencies in user behaviour sequences, outperforming traditional prediction methods in accuracy and robustness. Evaluations on real-world datasets validate its effectiveness.
Keywords
Movie Rating Prediction, Behaviour Sequence Transformer, OTT Platforms, Recommendation Systems, Machine Learning
How to Cite
Kethana, G., Manjudevika, M., “Rating Rate Prediction Using Behaviour Sequence Transformer for Movie Rating in OTT,” International Journal of Engineering and Techniques, Volume 10, Issue 3, June 2024. ISSN 2395-1303
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