DISSERTATION

Web based Recommender Systems and Rating Prediction

Abstract

This project implements a recommender system on large dataset of Netflix’s movies. This project also tries to improve recommender systems by incorporating confidence interval and genres of movies. This new approach enhances the performance and quality of service of recommender systems and gives better result than Netflix commercial recommender system, Cinematch.

Keywords:
Recommender system Computer science Web application World Wide Web Interval (graph theory) Information retrieval Quality (philosophy) Web service Service (business) Mathematics

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
15
Refs
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Recommender Systems and Techniques
Physical Sciences →  Computer Science →  Information Systems
Data Stream Mining Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Bandit Algorithms Research
Social Sciences →  Decision Sciences →  Management Science and Operations Research

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