Efficiency Analysis of Collaborative Based Recommendation System
Waleed Khalid, Xing Xing, Aikodon Julius, Yong Niu, Osama Tahir, Imran Ihsan · Journal of Physics Conference Series · 2020
Abstract Over the recent times, there has been great enhancement towards online shopping and platforms that provide commerce. Hence, great research and work has been done and is being done in field of recommendation systems. With this great development, there has been an exponential increase in online inventory due to the great number of users excessing these online platforms for buying and selling purposes and companies are often looking for advanced recommendation systems to provide their customers with the best online experience in respect towards each individual customer. It is believed that recent advancements in Deep Learning may provide an optimal solution for better recommendation systems, but it requires validation. The main aim of this paper is to follow through different research and investigate whether modern Deep Learning algorithms live up to the expectations and demands. Different reviews have been given in support with experiments. This literature review provides an analysis of different practices, state of the industrial methodologies and current research.