Proceedings of the 2023 4th International Conference on Big Data and Informatization Education (ICBDIE 2023)

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Quantitative Evaluation of Pharmaceutical Industry in Jilin Province Based on Text Mining

Authors
Liang Huo1, Chengyou Cui1, *
1College of Economic and Management, Yanbian University, Yanji, China
*Corresponding author. Email: cycui@ybu.edu.cn
Corresponding Author
Chengyou Cui
Available Online 26 September 2023.
DOI
10.2991/978-94-6463-238-5_80How to use a DOI?
Keywords
Pharmaceutical Industry Policy; Text Mining; PMC
Abstract

The pharmaceutical industry has evolved into one of the most strategically focused developing sectors as a result of the high prevalence of several epidemic viruses in recent years. Analysis of the effectiveness of Jilin Province’s pertinent pharmaceutical policies is necessary since the province is a significant source of medicinal resources in China with a wealth of herbal medicine reserves as well as clear advantages in the growth of the pharmaceutical industry. The text mining methods employed in this paper include LDA topic modelling, word frequency analysis, and keyword extraction. To visually analyze the policy themes and priorities of China’s pharmaceutical industry during the past ten years, 33 important pharmaceutical industry policies that were made public at the national level in that country between 2012 to 2022 are utilized as text mining objects. Along with pertinent references, the text mining results are used as a blueprint to create a more rigorous pharmaceutical industry assessment index system. Finally, we adopt the PMC model to quantitatively evaluate the key pharmaceutical policies issued by the Jilin government in recent years, analyzed the heterogeneity, strengths, and weaknesses of each key pharmaceutical policy in Jilin Province from a variety of dimensions and put forward reasonable suggestions for the improvement of relevant policies.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 4th International Conference on Big Data and Informatization Education (ICBDIE 2023)
Series
Advances in Intelligent Systems Research
Publication Date
26 September 2023
ISBN
978-94-6463-238-5
ISSN
1951-6851
DOI
10.2991/978-94-6463-238-5_80How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Liang Huo
AU  - Chengyou Cui
PY  - 2023
DA  - 2023/09/26
TI  - Quantitative Evaluation of Pharmaceutical Industry in Jilin Province Based on Text Mining
BT  - Proceedings of the 2023 4th International Conference on Big Data and Informatization Education (ICBDIE 2023)
PB  - Atlantis Press
SP  - 580
EP  - 598
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-238-5_80
DO  - 10.2991/978-94-6463-238-5_80
ID  - Huo2023
ER  -