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1704718PublishedVol 6 · Issue 12

FilmView: A Review Paper on Movie Recommendation Systems

Priyanshu Modi Atul Kumar Bhaskar Kapoor

Subject area: Science,Engineering and Technology  ·  Area of research: Recommendation Systems

Abstract

The proliferation of streaming platforms has led to a vast array of movie options, making it increasingly difficult for users to discover relevant Content. To address this challenge, recommendation systems have emerged as valuable tools for suggesting movies based on user preferences. We discuss the impact of temporal dynamics and social influence in improving recommendation accuracy and effectiveness. Moreover, we emphasize the importance of incorporating explanations to enhance user understanding and satisfaction. Through an examination of evaluation metrics, we assess the performance of these systems. Overall, this review contributes to the knowledge base, providing insights into the strengths, limitations, and future directions of Movie Recommendation Systems.

How to cite this paper

Priyanshu Modi, Atul Kumar, Bhaskar Kapoor "FilmView: A Review Paper on Movie Recommendation Systems" Iconic Research And Engineering Journals Volume 6 Issue 12 2023 Page 759-764
Priyanshu Modi, Atul Kumar, Bhaskar Kapoor "FilmView: A Review Paper on Movie Recommendation Systems" Iconic Research And Engineering Journals, vol. 6, no. 12, Jul. 2023
Priyanshu Modi, Atul Kumar, Bhaskar Kapoor (2023). FilmView: A Review Paper on Movie Recommendation Systems. Iconic Research And Engineering Journals, 6(12).
Priyanshu Modi, Atul Kumar, Bhaskar Kapoor "FilmView: A Review Paper on Movie Recommendation Systems" Iconic Research And Engineering Journals, vol. 6, no. 12, Jul. 2023.
@article{1704718,
      author = {Priyanshu Modi, Atul Kumar, Bhaskar Kapoor},
      title = {FilmView: A Review Paper on Movie Recommendation Systems},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {12},
      pages = {759-764},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704718.pdf},
      abstract = {The proliferation of streaming platforms has led to a vast array of movie options, making it increasingly difficult for users to discover relevant Content. To address this challenge, recommendation systems have emerged as valuable tools for suggesting movies based on user preferences. We discuss the impact of temporal dynamics and social influence in improving recommendation accuracy and effectiveness. Moreover, we emphasize the importance of incorporating explanations to enhance user understanding and satisfaction. Through an examination of evaluation metrics, we assess the performance of these systems. Overall, this review contributes to the knowledge base, providing insights into the strengths, limitations, and future directions of Movie Recommendation Systems.},
      month = {June},
  }