The Design of a Fuzzy Clustering Algorithm-Based Subsumption and Classification System for Digitized Chinese Language Teaching Resources

The purpose of this paper is to improve the feasibility and efficiency of the use of digital Chinese language teaching resources, to provide quality resources for Chinese language teaching more effectively, and to better meet the effect of user experience. By conducting requirement analysis, Designing functionality, developing systems, and implementing solutions, as well as system testing for the software system, a blueprint is put forward for a digital Chinese language teaching resources management system. Experimental results reveal a system stability of 95.37% and retrieval accuracy of 96.24%, demonstrating an 8.94% improvement over traditional methods. This system is proficient in delivering high-quality Chinese language teaching resources. Utilizing the proposed teaching resource system from this study is expected to enhance teaching effectiveness, alleviate learners' study load, and improve learning efficiency.