A Study on Product Recommendation System based on Deep Learning and Collaborative Filtering

This essay analyses and contrasts the literature that has already been written about various product recommendation systems and the mechanisms that underlie them. Although there are many research contributions in the literature, in this article I have critically and thoroughly examined recent research and review papers that are relevant to AI-based product recommendation systems. The present techniques are divided into groups based on the fundamental ideas included into their processes. The idea put out by the concerned writers, the experimental technique, and the performance assessment criteria are highlighted. Also noted are the researchers' assertions. The flaws that have been found are highlighted together with our results from the thorough literature study. This work is crucial for the comparison of different AI-based product recommendation systems, which is a necessary step before dealing with related problems. Following a review of the literature, I have put up a system for recommending products to users, in which the tool suggests products that a particular user would want to buy. I have gathered information about items and users by using ML algorithms. The suggested system establishes a link between the people and the products.