A survey of recommendation systems based on deep learning
Baichuan Liu, Qingtao Zeng, Likun Lu, Yeli Li, Fucheng You · Journal of Physics Conference Series · 2021
Abstract Faced with massive amounts of data, people may not be able to choose the items they like. The recommendation system came into being, and it has achieved a breakthrough for a long time. Using deep learning can mine the hidden attributes of users' items and integrate them well, bringing new changes to the recommendation system. This article describes the deep learning-based recommendation system and the traditional recommendation system, and analyzes their advantages and disadvantages.