Deep Reinforcement Learning-Based Recommender Algorithm Optimization and Intelligent Systems Construction for Business Data Analysis
Xingyu Fan, Lin Yang · 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) · 2022
Business analysis plays an essential role in numerous companies and industries, which involves data collection, data analysis, and the construction of intelligent systems to make critical business decisions. By using a data model to filter through consumers' data, it is easier than ever to make recommendations to consumers for what they would enjoy using or purchasing. Added a real-time product Recommendation System framework, the Reinforcement Learning model is used to automatically learn the optimal recommendation strategy. Also, the Deep Q-Network (DQN) algorithm is modified by replacing the convolutional neural network with the Long Short-Term Memory (LSTM). The solution analyzes and predicts consumers' preferences in real-time, and makes up for the lack of iterative optimization of traditional Recommendation Systems in real scenarios.