Paper
21 March 2023 Hotspots and trends of big data research in Chinese medicine based on text mining
Yao Yue, Xiaohong Cai, Jiayan Zhu, Yu Peng
Author Affiliations +
Proceedings Volume 12609, International Conference on Computer Application and Information Security (ICCAIS 2022); 126091V (2023) https://doi.org/10.1117/12.2671741
Event: International Conference on Computer Application and Information Security (ICCAIS 2022), 2022, ONLINE, ONLINE
Abstract
This paper uses text mining techniques to study the hotspots and trends of Chinese medicine big data research. This study retrieved literature related to “Chinese medicine + big data” from China Knowledge Network and Wan fang database as a collection of research documents. Using python3 and related toolkits, text mining was performed on the relevant literature. Through cluster analysis, we obtained the rules of medication and the construction of big data platforms for Chinese medicine, which have been the hotspots of research in recent years; using co-occurrence analysis, knowledge graph analysis and other big data-related techniques to study the rules of medication, the rules of formulae, the thinking on the application of big data in Chinese medicine, the current situation and the construction of platforms, which are still the future research trends. The use of text mining technology can provide an intuitive and systematic representation of current hotspots as well as future development trends, and can provide methodological summaries and ideas for the modernization and development of Chinese medicine.
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Yao Yue, Xiaohong Cai, Jiayan Zhu, and Yu Peng "Hotspots and trends of big data research in Chinese medicine based on text mining", Proc. SPIE 12609, International Conference on Computer Application and Information Security (ICCAIS 2022), 126091V (21 March 2023); https://doi.org/10.1117/12.2671741
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KEYWORDS
Medicine

Analytical research

Mining

Data mining

Evolutionary algorithms

Biomedical applications

Data storage

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