A Collaborative Recommender System Enhanced with a Neural Network
Vijayshri Nitin Khedkar, Nirav Raval · 2021
Nowadays, the creation of a recommendation system is a significant research area which attracts many researchers and scientists worldwide. Recommendation systems are wildly accepted in movies, songs, search queries and also in successful commercial products. In the recommendation system, the collaborative filtering approach is advantageous and robust. It also finds the close results, which helps to recommend an accurate movie to the end-user (Bobadilla J, 2013). Neural networks give a splendid output explicitly in this case. This paper represents the methodology which represents a different method to recommend a film to the users. We have built a simple neural network using Pytorch. The analysis on the benchmarks MovieLens 1M data set has shown drastic improvement over the state of the art recommendation system algorithm. The evaluation of the model is done using the mean square error (MSE).