Student Innovation and Entrepreneurship Guidance Under the Integration of Data Association and Internet

With innovation and entrepreneurship education occupying an increasingly important position in the higher education system, how to efficiently integrate educational resources, improve educational quality, and enhance students’ innovation ability has become a key issue that urgently needs to be addressed. In this context, the profound influence of Internet plus has become increasingly prominent, providing infinite possibilities for educational innovation. This paper focuses on the guidance of students’ innovation and entrepreneurship under the integration of data association and the Internet and explores a new education model. We constructed an educational resource model based on a clustering algorithm and applied it to the entrepreneurship analysis system of vocational colleges. This system can accurately analyze students’ entrepreneurial needs and potential, guide them to start their own businesses, promote the in-depth implementation of curriculum and professional reforms, and aim to achieve a significant increase in entrepreneurial rates. We conducted comparative experiments before and after data association to validate the statistical results of the new algorithm. The experimental results show that the new algorithm is not only feasible but also performs well in efficiency, significantly reducing the number of passes and scan records required for algorithm execution, thereby improving the efficiency and accuracy of educational resource integration. Through in-depth mining and analysis of massive educational resources and student behavior data on the Internet, we can more accurately grasp the entrepreneurial needs and learning characteristics of students and then provide more targeted and personalized education services.