关键词: 图挖掘, 频繁闭图, CloseGraph算法, 中医方剂学

Abstract:

On the basis of analyzing  the commonalities between the correlation of Traditional Chinese Medicines and the relationship of data nodes of the graph structure, we  transfered the links of the drugs in a prescription into the graph structure data according to the rules. Dealing  the structured prescription data with CloseGraph, an efficient frequent closed subgraph mining algorithm, we  got frequent closed graph with a specific function of the graph structure. And then we obtained the core drug combinations and the forms of the combinations with a decisive effect on a specific disease for Traditional Chinese Medicines, providing a valuable scientific basis on figuring out the principles among diseasesyndromeformula. We successfully introduced the graph mining strategy into the field of Chinese Medicine research, providing a new idea and a more solid scientific theoretical foundation for both the prescription study and the future development of Traditional Chinese Medicines.

Key words: graph mining, frequent closesubgraph, CloseGraph algorithm, Traditional Chinese Medicine formula