Design and Implementation of Chinese Traditional Medicine Association System Based on Improved Association Rules Algorithm

DOI

10.2991/ncce-18.2018.108How to use a DOI?

Keywords

Data mining; Association rule; Algorithm; Service system; Traditional Chinese medicine.

Abstract

As an important descriptive data mining method, association rules based on apriori algorithm have been widely used in the discovery of the core prescriptions of traditional Chinese medicine, and the correlations between symptoms and syndromes, syndromes and modern examination results, and symptoms and traditional Chinese medicine and other practical issues. However, we should see that the method of traditional association rules based on the frequent item set cannot fully reflect the complexity of traditional Chinese medicine. Chinese culture is an inclusive culture. Both effective and ineffective experience are written in the book. Many useful experiences are not frequently displayed. If the traditional association rules are followed, many important information will be abandoned. This study inherits the concept of support degree of traditional association rules, and adds the parameters of asymmetric relative degree (JACCARD) as a supplement to the frequent item set. The new algorithm is supported by the Python platform and the traditional Chinese medicine association service system has been finished, well-performed, able to discovery secret, yet valuable associative knowledge. The system is expected to find effective experiences from the experiences of Chinese history and contribute to the inheritance and innovation of Chinese medicine.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ruixiang Wang
PY  - 2018/05
DA  - 2018/05
TI  - Design and Implementation of Chinese Traditional Medicine Association System Based on Improved Association Rules Algorithm
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 663
EP  - 666
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.108
DO  - 10.2991/ncce-18.2018.108
ID  - Wang2018/05
ER  -