Data Matrix Mining Algorithm Optimization Promotes the Construction of a Decentralized Platform for Teaching Evaluation in Universities

Aiming at the shortcomings of the existing algorithms based on Apriori matrix, this paper proposes an improved algorithm based on Apriori compression matrix. The main work is the reform of college management and services, and the one-stop service for colleges and universities centered on teachers and students The platform began to be built one after another. In the context of the reform of "delegating power, delegating power, managing services", the construction, practice and exploration of one-stop service platforms in colleges and universities need to change their concepts and strengthen top-level design. The matrix size is greatly reduced, the number of candidate item sets is reduced, and the efficiency of mining frequent itemsets is improved. The algorithm has higher operating efficiency and scalability than existing matrix-based algorithms in mining intensive databases.