Recommendation System in Machine Learning

EasyChair Preprint 13177

Abstract

The goal of a recommendation system is to predict user
interests and infer their mental processes. Based on the
user's demands and while taking into account their
interests, this system can give them the information they
need. A more thorough analysis of the data is required
to provide better recommendations. Numerous
recommendation systems have been developed using
diverse methodologies. As OTT platforms, shopping,
travel, and other websites proliferate and strive to
quickly improve their user suggestions, the research
into such systems has gained popularity up to this point.
In this paper, we have implemented movies
recommendation system using machine learning
techniques. We have studied and compared different
recommendation models and using the best model we
have implemented the movies recommendation system
for recommending movies to the user. Machine
learning is used in the movies recommendation system
because it gives an entity the potential to learn
artificially without explicit programming

Keyphrases: Content filtering Collaborative filtering, Learning Movies Recommendation models, Recommendation System Machine

@booklet{EasyChair:13177,
  author    = {Ayush Hedaoo},
  title     = {Recommendation System in Machine Learning},
  howpublished = {EasyChair Preprint 13177},
  year      = {EasyChair, 2024}}