Network Teaching Technology Based on Big Data Mining and Information Fusion

Author:

Du Yishan1,Zhao Tianzhong1ORCID

Affiliation:

1. School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China

Abstract

With the continuous development of modern multimedia technology, the integration of computer technology into the teaching of various subjects has become a trend of the times. The application of computer media and network technology in mathematics teaching improves the integration of mathematics teaching and the integration of resources. A mathematics teaching network media fusion technology is proposed based on big data mining and information fusion, which combines the characteristics of multimedia and network technology in opening, creativity, subjectivity, and so on, and the database model of mathematics teaching is constructed. The multithread integrated scheduling method is used to design the mathematics teaching database model, the fuzzy control method is used to control the multimedia in mathematics teaching, and the big data association rule mining method is used to realize the information fusion of mathematics teaching resources. The optimization and integration of mathematics teaching resources and adaptive scheduling are realized under the technology of computer media and network, and the level of mathematics teaching is improved. The test results show that using this method to design the computer network media of mathematics teaching has a better ability of integrating and dispatching mathematics teaching resources, and the integration of mathematics teaching resources is stronger, which promotes the improvement of mathematics teaching level.

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

Reference27 articles.

1. Automatic Line Segment Registration Using Gaussian Mixture Model and Expectation-Maximization Algorithm

2. Task allocation mechanism for crowdsourcing system based on reliability of users;S. H. I. Zhan;Journal of Computer Applications,2017

3. Distributed time-sensitive task selection in mobile crowdsensing;M. H. Cheung

4. Reputation-based incentive mechanisms in crowdsourcing;L. L. Rui;Journal of Electronics & Information Technology,2016

5. Incentive Mechanism for Mobile Crowdsourcing Using an Optimized Tournament Model

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