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Bibliometric Analysis for Intelligent Assessment of Data Visualization

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Computer Science and Education (ICCSE 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1811))

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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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Authors and Affiliations

  1. School of Information Science, Beijing Language and Culture University, Beijing, China

    Jimei Li, Lai Chulin, Xinyu Li & Qian He

Authors
  1. Jimei Li
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  2. Lai Chulin
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  3. Xinyu Li
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  4. Qian He
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Corresponding author

Correspondence to Jimei Li .

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Editors and Affiliations

  1. Xiamen University, Xiamen, China

    Wenxing Hong

  2. Sichuan University, Chengdu, China

    Yang Weng

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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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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2442-4

  • Online ISBN: 978-981-99-2443-1

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