An intelligent drug matching method for traditional Chinese medicine

Chinese medicine prescription, being one of the mainstream medical method in traditional Chinese medicine, always contains complex complicated relationship between drugs which are hard to extract manually. However, with the rise of data-mining technology, it is more possible to finish such tasks intelligently with large scale text data. In order to discover the relationship between drugs, the relevance of prescription as well as attributes of drugs were quantified to establish the network model, then the state-of-art technologies in graph mining were utilized to study the matching rules of drugs in a specific prescription. Experiment results shows that our method could simulate results that are similar with the theoretical ones in traditional Chinese medicine and could be regarded as potential approach for automatic drug matching.