Review on unmanned retail recommender system based on deep learning user portrait

Abstract

As a data analysis tool, user portrait and recommendation system can deeply analyze and describe customers and commodity resources in unmanned retail industry. The situational fusion of them can provide a new idea for resource aggregation of unmanned retail recommendation system. By way of reading and sorting of the existing literature of unmanned retail recommendation system, the literature of unmanned retail recommendation system based on deep learning user portrait is systematically classified, described and evaluated from the aspect of convolutional neural network, providing a basic literature reference for the combination of deep learning user portrait and unmanned retail recommendation system. In the upcoming new retail industry, artificial intelligence connects the supply side and the demand side and will create a new retail system, which requires a lot of data and algorithms to support, but the resulting social problems also need to be solved. This paper aims at this social phenomenon and hopes to be helpful to subsequent readers.