Movie Recommender System

Registration ID: IJNRD_217326

Published ID: IJNRD2404324

DOI: Click Here to Get

S.Meena Kumari , Y. Sowmya , T. Vyshnavi , M. Rohini , T. Bhavitha

Collaborative filtering ,Recommendation ,Scalability ,Memory based ,Model based

Movie recommender systems play a crucial role in modern media consumption, aiding users in discovering new content tailored to their preferences. Collaborative filtering (CF) techniques, which leverage user-item interaction data to make recommendations, have gained significant attention due to their effectiveness in various domains, including movie recommendation. This paper presents a comprehensive review of collaborative filtering-based movie recommender systems, focusing on their methodologies, algorithms, evaluation metrics, and challenges. We explore different types of collaborative filtering approaches, including memory-based and model-based methods, highlighting their strengths and limitations. Furthermore, we discuss recent advancements such as hybrid approaches, deep learning-based CF models, and the incorporation of contextual information to enhance recommendation accuracy and diversity. Evaluation metrics and benchmark datasets commonly used in assessing the performance of movie recommender systems are also examined. Finally, we address challenges and future directions in the field, including scalability issues, cold-start problems, and the integration of explainability in recommendation systems.

Published Paper   E-Certificate

S.Meena Kumari, Y. Sowmya , T. Vyshnavi, M. Rohini, & T. Bhavitha (April-2024). Movie Recommender System . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), d192-d197. https://ijnrd.org/papers/IJNRD2404324.pdf

Volume 9 Issue 4, April-2024

Pages : d192-d197

Paper Reg. ID: IJNRD_217326

Published Paper Id: IJNRD2404324

Downloads: 000121985

Research Area: Computer Engineering 

Country: Ananthapur , Andhra Pradesh , India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404324.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404324

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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