Abstract
In the era of digital economy, high-quality visualization of data can better support decision making to show the value of data. In this paper, data visualization journal papers and conference proceedings papers were obtained through CNKI, and the annual number of published papers, literature sources, literature authors and hot keywords were counted. We have analyzed the statistical results from the whole to the specific order to get the current development status of data visualization and given the future development trend, especially for intelligent assessment of data visualization works, which can improve the popularization rate of data visualization, promote the development of data visualization technology, and give full play to the deep value of big data.
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Acknowledgment
This work was partly supported by Research on International Chinese Language Education of the Center for Language Education and Cooperation “Research on identification and influence of teaching methods of International Chinese Education based on classroom video” (No. 21YH11C), by New Liberal Arts Program of Ministry of Education (No. 2021180006), by New Engineering Program of Ministry of Education (No. E-SXWLHXLX 20202604), by the Cooperative Education Program of the Ministry of Education (NO. 202101110002), and by the Science Foundation of Beijing Language and Cultural University (supported by “the Fundamental Research Funds for the Central Universities”) (No. 22YJ080004).
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Li, J., Chulin, L., Li, X., He, Q. (2023). Bibliometric Analysis for Intelligent Assessment of Data Visualization. In: Hong, W., Weng, Y. (eds) Computer Science and Education. ICCSE 2022. Communications in Computer and Information Science, vol 1811. Springer, Singapore. https://doi.org/10.1007/978-981-99-2443-1_32
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DOI: https://doi.org/10.1007/978-981-99-2443-1_32
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