Abstract
To realize education informatization, it is highly necessary to recommend teaching resources to students that can enhance their learning interest and improve teaching quality. This paper develops a personalized matching system for management teaching resources based on collaborative filtering (CF) algorithm. Firstly, the authors set up a user interest model, designed the flow and algorithm for personalized matching, and improved the similarity calculation method. Next, a personalized recommendation algorithm was developed based on the CF, and a personalized matching engine was constructed with the aid of Apache Mahout. The experimental results show that the proposed CF algorithm can effectively improve the recommendation quality, and push personalized teaching resources to each user; the learners are highly satisfied with the personalized matching system. The research results shed new light on personalized recommendation of teaching resources, opening up a new way to education informatization.
Highlights
The rapid development of computers, information technology and network technology has changed the people’s way to live and learn, and set off a wave of education informatization in China
It can be seen that most learners are satisfied with the personalized matching system of management teaching resources based on collaborative filtering (CF) algorithm, indicating that the system can meet the learners’ personalized learning to a certain extent, and have a certain recommendation effect, but a small number of learners are still dissatisfied with the system, indicating that the system still needs to be continuously improved according to the needs of learners in the future
This paper applies the recommendation technology to the management teaching, and studies the personalized matching system of management teaching resources based on the CF algorithm
Summary
The rapid development of computers, information technology and network technology has changed the people’s way to live and learn, and set off a wave of education informatization in China. People can obtain more learning opportunities and resournces through the network, they still feel it more difficult to find the information they need quickly and effectively, so it is important to apply recommendation technology to the education field and provide learners with suitable teaching resources. The Open University Neitherland constructed a personalized recommendation system and summarized the application scenarios of various personalized recommendation technologies [3] In recent years, this technology has developed rapidly, and been used in almost every field. This technology has developed rapidly, and been used in almost every field Domestic websites such as JD.com, Alibaba, and Dangdang are mature in the application of personalized recommendation technology [4]. The experimental analysis was conducted to verify the effectiveness and practicability of the improved algorithm and personalized matching system
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