A Hybrid Approach to Movie Recommendation System

Abhay Yadav; Garima Srivastava; Dr. Sachin Kumar

doi:10.54060/a2zjournals.jmss.62

Authors

Abhay Yadav Amity School of Engineering and Technology, Amity University, Lucknow Campus, India
Garima Srivastava Amity University Lucknow Campus
Dr. Sachin Kumar Amity School of Engineering and Technology, Amity University, Uttar Pradesh, Lucknow, India

DOI:

https://doi.org/10.54060/a2zjournals.jmss.62

Keywords:

Recommendation System, Content-Based Filtering, Collabora-tive Filtering, Hybrid recommendation system

Abstract

Recommendation Systems (RS) have become indispensable in today's digital ecosystem, influencing decisions and experiences across several platforms. This paper delves deeply on RS, including its history, functionality, and relevance. It covers many aspects of RS, such as Content-Based and Collaborative Filtering, using examples from a variety of industries, including e-commerce and entertainment. The paper also describes and covers empirical analysis methodologies for comparing RS efficacy and providing a framework. By conducting a qualitative and quantitative analysis, compared these three recommendation systems i.e. content based collaborative and Hybrid. This mixed analysis approach was necessary as Content-Based Filtering systems are not easily quantifiable, and for a movie recommendation system, the qualitative aspect holds significant importance. Through our analysis, it became evident that a hybrid recommendation system consistently outperforms standalone methods in terms of recommendation accuracy and relevance.

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