Research And Application Of Data Mining Of Chinese Medicine Formula Compatibility Law Based On Complex Network

Traditional Chinese medicine(TCM)is the traditional medicine of the Chinese nation.It has been carried on and developed with the Chinese nation for thousands of years.In recent years,with the recognition and in-depth study of TCM,the modern study of TCM is no longer limited to the study of TCM itself and chemistry,pharmacology,pharmacology,biology,botany and even genomics have also carried out research around TCM.However,in today's information age,traditional Chinese medicine(TCM)has more and more information covering a wider range,and the work of sorting out and summarizing TCM is more and more complicated:how to use the huge knowledge of TCM prescriptions to effectively provide new compatibility of TCM prescriptions for TCM experts is an urgent problem to be solved.Data mining and complex network,as effective means of data processing and knowledge discovery,describe data respectively from the perspective of statistics and complexity,so they are widely used in modern TCM research.Therefore,this paper uses data mining and complex network to study the compatibility law of traditional Chinese medicine prescriptions,so as to establish a suitable research model for solving the compatibility problem of prescriptions.This paper has done the following work in the following three aspects:(1)the Apriori algorithm and FP-growth algorithm are used to study the compatibility rules of traditional Chinese medicine formulations,and the experimental results are compared and analyzed to compare the suitability of the two algorithms in the study of traditional Chinese medicine formulations.(2)the traditional Chinese medicine prescription network was successfully constructed based on the complex network.The traditional Chinese medicine prescription network for treating rheumatic diseases was taken as an example to construct the traditional Chinese medicine prescription network,and through comparative analysis with other common complex networks,it was demonstrated that the traditional Chinese medicine prescription network was a complex network,providing a scheme for the construction of traditional Chinese medicine prescription network.(3)use community discovery algorithm to conduct data mining of TCM prescription network.Compared with common community discovery algorithms,the improved COPRA algorithm is more suitable for the mining of TCM prescription network,providing algorithm support for the research of compatibility law of TCM prescription network(4)based on the complex network,the traditional Chinese medicine prescription relationship model was built,which successfully solved the problem that traditional formula mining could not reflect other properties of drugs,and provided a solution for the study of traditional Chinese medicine prescription law.(5)compare the research on formula rule based on complex network and the research on formula rule based on association rule,demonstrate the superiority of the two methods,and provide theoretical basis for the selection of formula rule research methods.