Year: 2024
Type: article
Abstract: Multimedia technology and big data have been widely used, which has had a profound effect on many traditional industries and greatly aided the field of education. In response to the enormous amount of digital information, how to efficiently mine it and identify its characteristics and laws has emerged as one of the research focuses in the discipline of scientometrics. It has brought new development opportunities for physical education (PE) in colleges and universities. In particular, the comparison of PE research in China and the United States and the lack of quantitative analysis of the frontiers and hot spots, the research on PE research results in China from the perspectives of scientometrics and information visualisation is currently still slightly insufficient. Therefore, using CiteSpace software, this paper analyses 946 English publications from the Web of Science and 232 Chinese publications from the Chinese Social Sciences Citation Index. It also visualises the information and performs cluster analysis. For researchers in the field of PE to compare the frontiers and hotspots of PE research in China and the United States over the previous five years, the knowledge map of PE research is presented and analysed. Then, starting with the fundamental idea of information systems, we present the support and significance of conditional attributes for decision attributes as heuristic data into genetic algorithms and suggest an IGA+ for knowledge that closely resembles the RS algorithm. The experimental results show that the IGA+RS algorithm is an effective knowledge abbreviation method that can further improve the efficiency of rough set knowledge abbreviation.
Source: Archive des Sciences
DOI: 10.62227/as/74s18
Authors: Liping Lang, Xiao Ma
Institution: Chengdu Sport University
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4401984043