Implementation of Movie Recommender System Based on Neo4J Graph Database

Implementation of Movie Recommender System Based on Neo4J Graph Database
Author(s):
Rakesh M B, Sri. B Naveen Kumar
Keywords:
COLLABRATIVE FILTERING, SIMILARITY, NEO4J
Abstract
With the frequent growth of Internet technology, information overload is place a major problem. By this huge data unable to fetch the useful information, to eradicate this issue search engines are came into existence but still the problem is not completely solve. Because of these issues Recommender systems are came into existence and they are use filtering technique, in this approach implement the Movie recommender system by using a cocept of traditional User based Collaborative filtering algorithm (UserCF). Here we get the user preferences and recommend the finest movie to the user. Meanwhile here we use a Neo4j Grpah database because of its huge advantage in dealing with the complex interconnected data and also handle a Bigdata.
Article Details
Unique Paper ID: 148442 Publication Volume & Issue: Volume 6, Issue 2 Page(s): 49 - 52
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org