Research on the Reform and Practice of Informatization Mode of Adult Higher and Continuing Education Academic Records Management in the Context of Three-Whole Parenting

Abstract

Information technology reform is an important way for schools to realize efficient management and information technology should be introduced into the management of student registration files to accelerate the process of informationization of registration file management. This paper builds an informatization database of adult higher continuing education student registration file management based on informatization technology and carries out the design of the main business process of student registration files. The multi-layer stacked LSTM network in the ELMo model is utilized to learn the preprocessing of the text of the school records data, and the CART decision tree algorithm is improved based on the reinforcement learning mechanism in order to improve the classification prediction accuracy of the decision tree in the dataset. In order to verify the feasibility of the school registration file informationization database constructed in this paper, a test analysis is conducted for the application of data mining technology and informationization database. The results show that the check accuracy of the CART decision tree algorithm improved by the reinforcement learning mechanism is around 80%, and the throughput of this paper’s database reaches 4827ops/s when the data writing volume is 1*105GB. When the number of threads reaches 128, the throughput of this paper’s informative database is around 5486ops/s, and when the data volume reaches 12*105 entries, the database in this paper the query response time is around 602ms. Under the background of three-round education, it is necessary to fully integrate information technology with the management of school registration files, which will lead to the innovation of the informationization mode of the management of school registration files in adult higher education.

Keywords

• elmo model
• lstm network
• reinforcement learning mechanism
• cart algorithm
• decision tree
• 00a35