Recommendations in E-Commerce Systems Based on Deep Matrix Factorization

Abstract

AbstractE-commerce systems (including online shopping, entertainment, etc.) play an increasingly important role and have become popular in digital life. These systems have also become one of the cores, and vital issues for many businesses, especially from the recent COVID-19 pandemic, the importance of online e-commerce systems are very necessary. Techniques in recommendation systems are widely used to support users in finding suitable products/items in online systems. This work proposes using deep matrix factorization for recommendation in online e-commerce systems. We provide a detailed architecture of a deep matrix factorization as well as make a comparison with the standard matrix factorization model. Experimental results on ten published data sets show that the deep matrix factorization model can work well for recommendations in online e-commerce systems.KeywordsDeep matrix factorizationMatrix factorizationRecommender systemsE-commerce systems