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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 11, ISSUE 5, MAY 2022

Movie Recommendation System Using Machine Learning

Sahil Chacherkar, Nilesh Nikhare, Akash Gawhane, Sagar Burade, Prof. Pratiksha Ramteke

DOI: 10.17148/IJARCCE.2022.11570

Abstract: In todays world ,the recommendation system are grownly important. Peoples now days finding out best services or products for themselves. Due to this, the recommendation system are important as they helping to make the right choice, without expending the cognitive resource. In this article, we aim to reduce human efforts by giving him the suggestion, to the users on the basis of their interest. we use Collaborative recommendation by implementing K-Nearest Neighbors algorithm. Collaborative filtering technique most widely used by recommendation system. Collaborative filtering predicts the user choice in item selection based on the known user rating of the items. It is effective for solving the information overload problem.’ Collaborative filtering can be divided into two main branches, Memory based collaborative filtering and model based collaborative filtering. Keyword: Recommendation System, Movie Recommendation System, KNN, Machine Learning.

How to Cite:

[1] Sahil Chacherkar, Nilesh Nikhare, Akash Gawhane, Sagar Burade, Prof. Pratiksha Ramteke, “Movie Recommendation System Using Machine Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2022.11570