Implementation of Movie Recommender System Based on Neo4J Graph Database

  • Unique Paper ID: 148442
  • Volume: 6
  • Issue: 2
  • PageNo: 49-52
  • 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.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{148442,
        author = {Rakesh M B and Sri. B Naveen Kumar},
        title = {Implementation of Movie Recommender System Based on Neo4J Graph Database},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {2},
        pages = {49-52},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=148442},
        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. },
        keywords = {COLLABRATIVE FILTERING, SIMILARITY, NEO4J},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 6
  • Issue: 2
  • PageNo: 49-52

Implementation of Movie Recommender System Based on Neo4J Graph Database

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