Analysis of Netflix Recommendation System

The recommendation engines utilized by Netflix provide an extensive array of content. The algorithms employed by Netflix play a vital role in assisting users in discovering the material they seek. Numerous recommender systems are available that deliver valuable suggestions for various products and services. The recommendation algorithms of Netflix are grounded in machine learning and utilize information filtering techniques to anticipate user ratings and preferences for specific Netflix offerings or products. The term recommendation systems are often used in a pejorative sense to describe recommender systems. Generally, there are four primary categories of recommendation systems: content-based, collaborative filtering, simple recommendation systems, and hybrid methods.

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Publication Details

Journal
International Journal of Innovative Research in Advanced Engineering
Published
2024-12-06
DOI
https://doi.org/10.26562/ijirae.2024.v1111.10
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of Netflix Recommendation System

Abhishek Kumar, Vibhor Gupta, Ashish Kumar Jha, Aman Kumar et al.
International Journal of Innovative Research in Advanced Engineering
Technology and Data Analysis
article

Analysis of Netflix Recommendation System

Abhishek Kumar, Vibhor Gupta, Ashish Kumar Jha, Aman Kumar, Harshit Sharma
article en

Abstract

The recommendation engines utilized by Netflix provide an extensive array of content. The algorithms employed by Netflix play a vital role in assisting users in discovering the material they seek. Numerous recommender systems are available that deliver valuable suggestions for various products and services. The recommendation algorithms of Netflix are grounded in machine learning and utilize information filtering techniques to anticipate user ratings and preferences for specific Netflix offerings or products. The term recommendation systems are often used in a pejorative sense to describe recommender systems. Generally, there are four primary categories of recommendation systems: content-based, collaborative filtering, simple recommendation systems, and hybrid methods.

International Journal of Innovative Research in Advanced EngineeringVol. 11(11)
Openalex Percentile: Top 65%
Technology and Data Analysis
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Analysis of Netflix Recommendation System — Abhishek Kumar, Vibhor Gupta, et al. · International Journal of Innovative Research in Advanced Engineering (2024) | TGRS Research Map | TGRS