Research on Personalized Recommendation Model and algorithm in deep learning mode
Feng Liu, Yingjie Song, Yuhui Han, Mingyang Wu, Wei Dong, Ping Cai, Chang-hui Long, Bing-qian Wang · 2020
In order to improve the recommendation accuracy in collaborative filtering, this paper introduces deep learning into the recommendation algorithm, and proposes a personalized recommendation model and algorithm under the deep learning mode. Firstly, the advantages and disadvantages of common algorithms are analyzed; then, the deep learning mode is constructed, and the deep learning is integrated into the recommendation algorithm step by step; finally, the simulation data are verified by cosine similarity and probability based recommendation method, and the results show that the two methods get almost the same score, and get better recommendation results, which can effectively improve the recommendation progress and quality.