A University Innovation and Entrepreneurship Information Sharing Platform Based on Data Mining and Classification Algorithms

To improve the efficiency of university innovation and entrepreneurship education, this paper constructs an innovation and entrepreneurship information sharing platform based on data mining classification algorithm. And tested the platform, in the experiments, the data acquisition time interval of 100 and 600 seconds and the training set size, the length of the big data distribution and the width of the intelligent scheduling symbol are 2100 ms and 0.15 ms. The experimental results show that the data mining algorithm based on user feature data can reduce the sparsity of the user evaluation matrix to a certain extent. The sparsity of the traditional data mining algorithm is about 86.3%, and the matrix sparsity is reduced to 71.2% after the improved algorithm. With the gradual increase of user data, the data processing capabilities of innovation and business data sharing platforms are also increasing. Through testing, it is found that the currently selected data mining algorithm and its optimization steps are effective, which can be improved based on the traditional data mining algorithm to help the recommendation system to produce better results. Data mining classification algorithm plays an important role in college students ‘innovation and entrepreneurship, and further promotes the upsurge of college students' innovation and entrepreneurship.