MACHINE LEARNING APPROACHES FOR PERSONALIZED MOVIE RECOMMENDATIONS

MACHINE LEARNING APPROACHES FOR PERSONALIZED MOVIE RECOMMENDATIONS

Registration ID: IJNRD_194284

Published ID: IJNRD2305204

DOI: Click Here to Get

Prayank Vachhani , Prof. Ranjana Singh

Digital media content, Machine learning algorithms, State of the systems, CollaborativeFiltering, Evaluation metrics

With the increasing amount of digital media content, movie recommendation systems have become essential in helping users find movies or TV shows that match their interests and preferences. These systems use machine learning algorithms to analyze user data, including their viewing history, ratings, and other relevant factors, to generate personalized recommendations. In this research paper, we provide an overview of movie recommendation systems, including their types, challenges, and state-of-the-art approaches. We also discuss how these systems are implemented in various platforms and their impact on user engagement and satisfaction. Finally, we present a case study of a collaborative filtering-based movie recommendation system using Python and evaluate its performance using different evaluation metrics.

Published Paper   E-Certificate

"MACHINE LEARNING APPROACHES FOR PERSONALIZED MOVIE RECOMMENDATIONS", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 5, page no.c21-c25, May-2023, Available :https://ijnrd.org/papers/IJNRD2305204.pdf

Volume 8 Issue 5, May-2023

Pages : c21-c25

Paper Reg. ID: IJNRD_194284

Published Paper Id: IJNRD2305204

Downloads: 000121155

Research Area: Engineering

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305204.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305204

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

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

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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