Abstract

With the rapid development of computer and network technology, the Internet has gradually entered people's daily life and completely changed the way people obtain information. Massive network information provides a guarantee to meet the information needs of users and brings great convenience to people. However, the diversity and variability of network information lead to the excessive expansion of information and the problem of information overload, which makes it difficult for people to find the required information from the vast information resources quickly and accurately. Therefore, the storage of courseware resources on the education cloud platform has increased sharply, resulting in the problem of "information overload" in the user learning stage. For users, relying solely on early classification and keyword retrieval technology is difficult to find the required courseware efficiently and accurately. Under this background, the online education resource recommendation system came into being, which has brought effective solutions to the above problems. This paper focuses on the design of Network Education Resource Recommendation Algorithm Based on collaborative algorithm, and completes the analysis and design work. The online education resource recommendation system customizes personalized recommendation services for users according to their individual characteristics, so that users can get what they are interested in more quickly and conveniently, and the collaborative recommendation algorithm is the core part of the system. At present, collaborative recommendation algorithm is the most widely used and studied recommendation algorithm, but the algorithm itself has problems such as sparse user rating data and cold start when new users join. Therefore, the research on collaborative recommendation algorithm is mainly focused on this problem. "Network Education Resource Recommendation System" is an intelligent system proposed to better realize network education.

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