Visual Analysis of Heterogeneous Data for Academic Planning
Conference: ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application
12/17/2021 - 12/19/2021 at Shenyang, China
Proceedings: ICMLCA 2021
Pages: 5Language: englishTyp: PDF
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Authors:
Zhao, Junhe; Li, Jin; Ding, Shili (Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang, China & University of Chinese Academy of Sciences, Beijing, China)
Li, Xu (Beijing Zhongke Zhihe Digital Technology Co., Ltd, Beijing, China)
Abstract:
With the reform of the new college entrance examination, provinces have successively implemented the new college entrance examination system, and colleges and universities recruit students according to subject types and majors. For middle school students, academic planning has become an important part of their middle school career, academic career planning mainly guides students to choose college entrance examination subjects and determine future university majors, as well as give targeted opinions on future careers. Visual analysis of students generates large amounts of heterogeneous data. This paper designs a method that can integrate multi-source heterogeneous data and use data visualization methods, such as radar charts, force-guided maps, word cloud methods, etc., to visually analyze the content of academic planning to assist decision-makers to better guide middle school students to make choices.