Hybrid Movie Recommender System

Authors

  • Pushpa Ganapati Padti Student, Department of Computer Science and Engineering, Srinivas Institute of Technology, Mangalore, India
  • Kavya Hegde Professor, Department of Computer Science and Engineering, Srinivas Institute of Technology, Mangalore, India
  • Prasanna Kumar Student, Department of Computer Science and Engineering, Srinivas Institute of Technology, Mangalore, India

Keywords:

Collaborative-based filtering, Content-based filtering, Hybrid model

Abstract

The need for Recommendation Systems is increasing day by day as companies using recommender systems focus on increasing sales as a result of very personalized offers and an enhanced customer experience. Recommendations typically speed up searches make it easier for users to access the content they’re interested and surprise them with offers they would have never searched for. This paper demonstrates the usage of machine learning algorithms in the movie recommender system. In this paper, we have introduced two types of filtering, content-based and collaborative-based filtering. Furthermore, we have given the analysis of the hybrid model.

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Published

25-07-2021

How to Cite

[1]
P. G. Padti, K. Hegde, and P. Kumar, “Hybrid Movie Recommender System”, IJRESM, vol. 4, no. 7, pp. 311–314, Jul. 2021.

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Section

Articles