Research on Collaborative Filtering Personalized Recommendation Algorithm Based on Deep Learning Optimization
In order to improve the accuracy of the project in the recommendation process, the article compares the existing content based and collaborative filtering recommendation calculations, makes full use of the advantages of different algorithms, and proposes a collaborative filtering personalized recommendation algorithm based on deep learning optimization. Through the deep learning training of users' preferences, the corresponding parameters are adjusted to establish a personalized recommendation method. Through experimental verification, the proposed algorithm can effectively improve the quality of personalized recommendation.
2019 International Conference on Robots Intelligent System (ICRIS)