• Nayana K Y
• Sudheeksha Herle V
• Tejaswini M
• Veekshitha Shetty
• Deepthi Dsouza, Dr.Suresha D

In the contemporary era, movies remain one of the most prevalent forms of entertainment, supported by significant advancements in production, creation, and distribution technologies. With the exponential growth in available content, users often face difficulty in selecting suitable movies, creating a strong need for intelligent recommendation systems. Emotion-Based Movie Recommendation Systems (E-MRS) address this by tailoring suggestions according to a user’s current emotional state. Emotions, being complex and deeply personal reactions to various stimuli, pose a challenge in developing accurate models for recommendation. This study introduces a novel approach that leverages color psychology to identify and interpret emotional states such as joy, sadness, anger, fear, and excitement. By allowing users to select a color corresponding to their mood through an intuitive interface, the system can infer their emotional condition and generate appropriate movie recommendations. The recommendation engine employs a hybrid technique that integrates collaborative filtering, which considers user behavior and preferences, with content-based filtering, which analyzes movie attributes. This combination enhances the system’s ability to provide personalized and emotionally relevant suggestions, ultimately aiming to improve user satisfaction and engagement.

Movie Recommendation, Color Psychology, Emotion Recognition, Collaborative Filtering Technique, Content-Based Filtering Technique.

"MOODMATCH MOVIES USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.425-431, July-2025, Available :http://www.jetir.org/papers/JETIRGX06079.pdf

"MOODMATCH MOVIES USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp425-431, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06079.pdf