International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Emotion Based Content Recommendation System Using Deep Learning

Abstract

This project aimed at developing an Emotion Based Content Recommendation System using Deep Learning to provide personalized content suggestions based on users' emotional states. The system is built to an analyze facial expressions in real time using Convolutional Neural Networks (CNN), which can accurately identify emotions such as joy, sorrow, anger, and others. Once an emotion is detected, the recommendation engine aligns it with suitable music and movie suggestions to match the user's current mood, thereby enhancing their overall experience.

By bridging the gap between emotion recognition and content personalization, the system creates an intuitive and mood driven entertainment experience. The core of this project is the CNN model that enables high precision emotion detection, while the recommendation module ensures that users receive relevant and emotionally resonant content. This project demonstrates the potential of AI in reshaping how users interact with digital media by adapting to their emotional needs and increasing engagement.

Built as an intelligent recommendation system, it offers not only enhanced content discovery but also a more personal and satisfying interaction with multimedia platforms. In short, this project aims to highlight the practical application of CNNs in emotion recognition and the importance of adaptive systems in modern entertainment.

Country : India

1 Priyanshu Gupta2 Sanskruti Ruke3 Sakshi Singh4 Sakshi Wasekar5 Rahul Jiwane

  1. Student, Information Technology, MCT Rajiv Gandhi Institute of Technology, Mumbai, India
  2. Student, Information Technology, MCT Rajiv Gandhi Institute of Technology, Mumbai, India
  3. Student, Information Technology, MCT Rajiv Gandhi Institute of Technology, Mumbai, India
  4. Student, Information Technology, MCT Rajiv Gandhi Institute of Technology, Mumbai, India
  5. Professor, Information Technology, MCT Rajiv Gandhi Institute of Technology, Mumbai, India

IRJIET, Volume 9, Issue 4, April 2025 pp. 215-218

doi.org/10.47001/IRJIET/2025.904031

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References

  1. Gaurav Dhiman, Deepak Jha, “Hybrid Deep Learning Model for Real Time Emotion Recognition from Facial Expressions.”(2023).
  2. Ahsan Jamil, Muhammad Naeem, "An Overview of Deep Learning Approaches for Facial Expression Based Emotion Recognition." (2022).
  3. Ajay Kumar Sahu, Sudip Ghosh, "A Comprehensive Review of Deep Learning Techniques in Facial Expression Recognition." (2022).
  4. Mohammad Nur Mollah, Md. Mahmud, "A Review of Deep Learning Based Techniques for Facial Expression Recognition." (2021).
  5. Jie Zhao, Jing Zhang, Hong Xu, "Deep Learning Approaches for Recognizing Facial Emotions." (2021).
  6. Marcio Cardoso Barros, Eliane Pires, "Real Time Facial Expression Based Emotion Recognition with Deep Learning." (2020).
  7. Sanke, M., et al. 'Emotion based Movie Recommendation System using Deep Learning', Research-Gate. (2023).
  8. Barros, M.C. and Pires, E. 'Real Time Facial Expression Based Emotion Recognition with Deep Learning', Journal of Neonatal Surgery. (2020).
  9. Jamil, A. and Naeem, M. 'An Overview of Deep Learning Approaches for Facial Expression Based Emotion Recognition'. (2022).
  10. Abhishek Choudhary, Anil Kumar, "Emotion Detection through Facial Expressions Using Deep Learning." (2022).

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