Design and application of educational information management system based on SOA

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Liping Han
Keyword(s):  
Information Management ◽  
Management System ◽  
Information Management System ◽  
Educational Information ◽  
Design And Application

scholarly journals Design and Application of Information Management System Based on ASP.NET

2012 ◽  
Vol 6-7 ◽  
pp. 948-951 ◽  
Author(s):  
Guang Zhao ◽  
Hong Yuan Huang
Keyword(s):  
Information Management ◽  
Staff Training ◽  
Management System ◽  
Office Automation ◽  
Information Management System ◽  
New Method ◽  
Work Efficiency ◽  
Design Project ◽  
Design And Application

With ASP.NET and ADO.NET technologies the staff training information management system was developed, realize the network office automation, make the information management betimes, and improve the work efficiency. The function peculiarity and design project of the system were discussed deeply, and put forward a new method of ASP.NET application.

Application of English education information management system based on convolution neural network classification algorithm

2020 ◽  
pp. 002072092094061
Author(s):  
Shubo Zhao ◽  
Zheqian Su ◽  
Guoxin Miao
Keyword(s):  
Neural Network ◽  
Information Management ◽  
Management System ◽  
English Education ◽  
Information Management System ◽  
Classification Algorithm ◽  
Convolution Neural Network ◽  
Neural Network Classification ◽  
Text Feature ◽  
Educational Information

In order to improve the convenience of English education management and improve the quality of teaching, this paper proposes the application of English education information management system based on convolution neural network classification algorithm. Specifically, it relies on spark cloud technology and data mining technology of cash to build an English education information management system. Secondly, in the educational information management platform, convolution neural network classification algorithm is used to mine useful information. Convolution network mainly combines the emotional words, parts of speech, degree adverbs, negatives, punctuation and other word features that affect the emotional tendency of the text to form an extended text feature. Then, the word vector feature and the extended text feature are used as two input channels of convolution neural network, and the dynamic K-max pooling strategy is adopted to improve the ability of feature extraction of the model. The experiment in the English education information management system shows that the classification performance of the algorithm in this paper is not only higher than that of the single channel convolution neural network algorithm, but also has some advantages compared with some representative algorithms. In addition, experiments verify the effectiveness of the educational information management system.

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