Recommendation System with Implicit Feedback

Abstract

A recommendation system is a field of information retrieval that helps users choose the right item among many choices available and helps a user save their time. The user interacts with objects of different domains, and the domains can be research papers, news articles, food recipes, job opportunities, friend suggestions, movies, music, games, etc. Recommendation systems are an integral part of the significant revenue of major technological companies offering various services to their users and enhancing their user experience. The role of a recommendation is to provide a small set of items that a user is likely to choose. In this work, we aim to increase the accuracy of these recommendations on popular data sets by providing a novel architecture of the system.