Abstract

This paper focuses on the construction of personalized education resource recommendation system and the research of key technologies in the big data environment, designs a personalized recommendation system architecture that can handle PB education resources, and implements an educational resource personalized recommendation system based on this architecture. A hybrid recommendation algorithm based on content and collaborative filtering is designed to meet the recommendation novelty requirements and solve the cold start problem of the recommendation system. Research a flexible, reliable, high-performance personalized recommendation system architecture that can store and process PB-level data and can be recommended in real time, research personalized recommendation engine, data pre-processing and data mining model construction, and implement the recommendation system. It is important to determine the availability of the system by performing related functions and performance verification.

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