BIG DATA MINING ALGORITHM OF CIVIC EDUCATION COURSE RESOURCES ORIENTED TO PROFESSIONAL LITERACY

Chunlei Lin
Department of Education and Engineering, Zhejiang Guangsha Vocational and Technical University of Construction,dongyang,China,322100
Junhui Zhou
Department of Public Physical Education, Zhejiang Guangsha Vocational and Technical University of Construction,dongyang,China,322100
Guangyong Pang, Xinping Yu
School of Intelligent Manufacturing,Zhejiang Guangsha Vocational and Technical University of Construction,dongyang,China,322100

Abstract:

Every minute, massive volumes of data are generated. Some data sources, such as those provided on the Internet, are self-evident. Throughout the day, social networking sites, search and retrieval engines, media sharing sites, stock trading sites, and news sources store massive volumes of new data. The term "big data" refers to any collection of data that is so huge and complicated that typical database management systems and data processing tools struggle to handle it. Diebold published the first research article on "big data" in 2000. Social networking sites, e-commerce portals, sensors (smart devices/IoT), and other sources of big data. The main aim of this study is to assess the Big Data Mining Algorithm of Civic Education Course Resources Oriented to Professional Literacy. This article compares traditional techniques based on BDA technology to the practical link, method innovation, and implementation path between BDA technology and civic education source resources methods. Experimental research demonstrates that when compared to traditional techniques, the performance of a civic education course based on data mining (D M I) in the context of B D A is more than 20% higher, demonstrating its practicality and highlighting the need for traditional methods to be innovated.