Research on Intelligent Recommendation of Learning Resources Based on Collaborative Filtering Algorithm

With the rapid development of Internet and information technology, knowledge data information is exploding. How to quickly find out the learning resources that learners are interested in or most in need from massive data information and recommend these resources to learners according to their characteristics is of great practical significance for improving learners' learning efficiency and learning effect. Online learning is an important way to acquire knowledge at present. However, information overload makes it very difficult to find the required learning resources from a large number of resources of online learning platform. Learning is a step-by-step process, and there is a certain contextual relationship between learning resource objects. This relationship can't be marked by a large number of people alone, but it should be built independently and intelligently. In order to solve this problem, recommendation technology came into being. According to different recommendation algorithms, the recommendation system can be divided into content-based recommendation, collaborative filtering recommendation, hybrid recommendation and so on. Among them, collaborative filtering recommendation is the most widely used recommendation algorithm. Scholars' rapid and accurate access to the required literature information has a direct impact on the efficiency and success of scientific research and teaching. This paper describes the Learning Resource Recommendation of collaborative filtering algorithm.