Design and Optimization of Lin Chaoxian's Directorial Movie Recommendation System Based on Plot Analysis and Emotion Recognition

Authors

  • Zhengliang Zhang Art Department, International College, Krirk University, Bangkok 10220, Thailand
  • Xuejun Guo Art Department, International College, Krirk University, Bangkok 10220, Thailand

Keywords:

LIN CHAOXIAN'S Model, Recommender Model, Whale Optimization, Emotional Intelligence, Plot Analysis, Machine Learning

Abstract

In this paper presented Lin Chaoxian's Directorial Movie Recommendation System, a cutting-edge application that revolutionizes the way audiences experience movies. Drawing upon the convergence of filmmaking and artificial intelligence, proposed system, the Whale Recommender Emotional Intelligence (WREI), incorporates sophisticated plot analysis and emotion recognition to deliver personalized and emotionally resonant movie recommendations. The WREI system begins with a robust plot analysis, where intricate details of movie plots, character interactions, and thematic elements are dissected using advanced natural language processing and machine learning techniques. This comprehensive analysis goes beyond mere genre classification, enabling the system to identify underlying themes and emotional content within each film. Emotion recognition, the second critical component of WREI, utilizes state-of-the-art computer vision and audio processing to discern emotional cues from the audience during movie viewing. Through analyzing facial expressions, vocal intonations, and physiological responses, the system accurately gauges viewers' emotional states throughout the film. The true power of WREI emerges when plot analysis and emotion recognition synergize. The recommendation system aligns the emotional journey of each film with the viewer's emotional preferences and current state. This innovative approach goes beyond conventional genre-based recommendations, offering movie suggestions that evoke the desired emotional response in the viewer, creating a deeply immersive and emotionally fulfilling movie-watching experience. Furthermore, WREI is designed to continuously learn and evolve with user interactions. As users engage with the platform and provide feedback, the AI refines its understanding of their emotional preferences, enabling even more personalized and spot-on movie recommendations over time.

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Published

30.11.2023

How to Cite

Zhang, Z. ., & Guo, X. . (2023). Design and Optimization of Lin Chaoxian’s Directorial Movie Recommendation System Based on Plot Analysis and Emotion Recognition. International Journal of Intelligent Systems and Applications in Engineering, 12(6s), 326–339. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3980

Issue

Vol. 12 No. 6s (2024)

Section

Research Article

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