Common neighbor similar triangle agglomeration-based hierarchical and overlapping community discovery method applicable to traditional Chinese medicine herbs (TCMF) network

Abstract

The invention provides a common neighbor similar triangle agglomeration-based hierarchical and overlapping community discovery method applicable to a traditional Chinese medicine herbs (TCMF) network. The method comprises the following steps: 1) common neighbor similar triad agglomeration stage a: seeking all triads; b: calculating the similarity of any two triads; c: giving a similarity threshold of the triads, and merging the triads with the similarities which are higher than the similarity threshold as initial communities; and d: ending; and 2) cluster merging stage a: calculating the distance between any two initial communities; b: setting a distance threshold of the initial communities, and merging the two initial communities with the distance which is smaller than the distance threshold; and c: ending. The TCMF network-based hierarchical and overlapping core medicine group discovery method provided by the invention provides a new method for TCMF network discovery; and by adopting the method, a high overlapping and hierarchical medicine group community structure of the TCMF network can be excavated by setting three parameters alpha, beta and gamma, and a solution is provided for core medicine group discovery in prescription compatibility.

Description

technical field [0001] The present invention relates to a method for mining Traditional Chinese Medicine Herbs (TCMF for short), in particular to a method for discovering hierarchically overlapping communities based on the agglomeration of common neighbors and similar triangles, which is applicable to TCMF networks. Background technique [0002] At present, there are three main modes of research on the compatibility of prescriptions using data mining technology: classification-based data mining research mode, cluster-based data mining research mode and association rule mining-based research mode. [0003] Using the network point of view to describe the objective world originated in 1736 when the German mathematician Eular solved the problem of the seven bridges of Königsberg. Using the topology of the network to mine its functional modules and organizational structure is the main goal of community structure discovery. So far, a large number of researchers have invested a lot...

AI Technical Summary

Problems solved by technology

Traditional hierarchical overlapping community discovery methods (such as LFM method, edge agglomeration method, etc.) are not suitable for TCMF networks

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