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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | Emotion-Driven Movie Recommendation System: Integrating Emotion Detection Techniques for Enhanced User Experience |
| Authors Name: | Aarin Luwaria , Jagdeep Mahala , Alok Raj , Saurabh Raj |
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IJRTI_189681
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| Published Paper Id: | IJRTI2404113 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | In this paper, we propose an emotion-driven movie recommendation system that integrates emotion detection techniques to enhance the user experience. Traditional movie recommendation systems primarily rely on user preferences and historical data, often overlooking the emotional aspect of movie consumption. Emotions play a crucial role in determining individual preferences and satisfaction levels while watching movies. Therefore, our research focuses on incorporating emotion detection algorithms to analyse movie content and user reactions, thus providing personalised recommendations based not only on genre or ratings but also on emotional resonance. We begin by reviewing existing literature on movie recommendation systems and emotion detection techniques. Subsequently, we describe our methodology, including data collection, preprocessing, feature extraction, and recommendation algorithm design. We also discuss the challenges and limitations associated with emotion detection in movie content. Through implementation and evaluation, we demonstrate the effectiveness of our proposed system in providing accurate and personalized movie recommendations. Our findings indicate that integrating emotion detection significantly improves recommendation quality and user satisfaction. We conclude with a discussion on the implications of our research, including potential applications and future directions in emotion-driven recommendation systems. |
| Keywords: | Collaborative filtering, personalized, machine learning, deep learning, user interaction, emotional cues, engagement, satisfaction, media consumption behavior, advanced algorithms, real-world datasets, relevance, user preferences. |
| Cite Article: | "Emotion-Driven Movie Recommendation System: Integrating Emotion Detection Techniques for Enhanced User Experience", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.812 - 817, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404113.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2404113
Registration ID:189681
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 812 - 817 Country: Jaipur, Rajasthan, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2404113 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2404113 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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