Intelligent Search and Matching Method for Innovation and Entrepreneurship Teaching Cases in Universities Based on the Twin Bert Model

Intelligent Search and Matching Method for Innovation and Entrepreneurship Teaching Cases in Universities Based on the Twin Bert Model

This article combines artificial intelligence algorithms and uses the Bert model to search for suitable innovation and entrepreneurship teaching cases to assist in the development of relevant courses. The effectiveness of the model depends on the establishment of databases and data labels. Therefore, this article first conducts data statistics and analysis for the target universities, and structurally designs a network questionnaire. Based on the results of the network questionnaire, the root mean square and error analysis methods are used to evaluate the student’s ability. The chi square value and Pearson coefficient are used to evaluate the innovation and entrepreneurship level at the school level, providing a reasonable data input layer for the Bert model’s intelligent matching. Students can obtain targeted tutoring resources by entering keywords. Finally, according to the existing resource conditions of vocational colleges, this article proposes to connect with the data of the electronic reading room on campus, and the integrated system is added. Expert review function module, Timely correction of student projects.