Research on WeChat Applet Intelligent Assistant based on Intelligent Recommendation Algorithm

This article conducts in-depth research on the intelligent assistant function in WeChat mini programs based on intelligent recommendation algorithms. By analyzing user behavior data and preferences, and utilizing machine learning and data mining techniques, personalized recommendation functions have been implemented. This intelligent assistant selects corresponding recommended content from a large number of WeChat mini programs based on user history, interests, social relationships, and other information, and provides it to users. By introducing a recommendation system, the user experience of WeChat mini programs has been significantly improved. This study used the gpt-3.5-turbo model as the core of the intelligent recommendation algorithm. The model has strong Natural language processing and reasoning capabilities, can understand the needs of users, and generate relevant recommendation information according to the context. In the experiment, we collected a large amount of user data for training and testing, verifying the effectiveness and accuracy of the algorithm. The experimental results show that the intelligent assistant of WeChat applet based on intelligent recommendation algorithm can better meet users' interests and needs when providing recommendation content, and effectively increase users' Click-through rate and satisfaction. At the same time, intelligent assistants can also adjust and optimize in real-time based on user feedback and interactive data, providing more accurate and personalized recommendation services.