Research Article
High Quality Resources Sharing of College Students’ Career Guidance Course Teaching Based on Decision Tree Classification Algorithm
@INPROCEEDINGS{10.1007/978-3-031-50543-0_26, author={Meiling Ou}, title={High Quality Resources Sharing of College Students’ Career Guidance Course Teaching Based on Decision Tree Classification Algorithm}, proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part I}, proceedings_a={ADHIP}, year={2024}, month={3}, keywords={Decision Tree Classification Algorithm College Student Career Guidance Courses Teaching. High Quality Resource Sharing}, doi={10.1007/978-3-031-50543-0_26} }- Meiling Ou
Year: 2024
High Quality Resources Sharing of College Students’ Career Guidance Course Teaching Based on Decision Tree Classification Algorithm
ADHIP
Springer
DOI: 10.1007/978-3-031-50543-0_26
Abstract
In order to improve the quality and efficiency of sharing high-quality teaching resources and achieve ideal results, a decision tree classification algorithm based method for sharing high-quality teaching resources in college student employment guidance courses is proposed. Firstly, before resource sharing and transmission, design a security key for public information and encrypt the public information of high-quality teaching resources. Secondly, the decision tree classification algorithm is used to construct a classification standard for electronic archives, and regional partitioning is performed to extract resource sharing classification codes. At the same time, establish a database of teaching resources for employment guidance courses to store information related to high-quality teaching resources for college students’ employment guidance courses. Finally, establish a blockchain based teaching resource security sharing model to achieve information sharing of high-quality teaching resources. Experimental analysis shows that the proposed method can complete the high-quality resource sharing task of college student employment guidance course teaching within 5–8.5 ms after application, with a significant advantage in resource sharing efficiency.
