Overlapping community discovery method based on multi-triangular group similarity aggregation for tcmf network

Abstract

The present invention provides a method for discovering overlapping communities based on similarity aggregation of multi-triangular groups applicable to TCMF networks, comprising the following steps: 1) searching for an initial community stage: a. finding a center point, and initializing a community; b searching for a multi-triangular group, Join the initial community; c Repeat the above steps until the degree of the central point is less than the threshold; d Add unassigned nodes to the initial community; e End; 2) Merge the initial community stage: a Calculate the similarity between every two communities ; b select the two most similar communities to merge; c repeat the above steps until the end. The overlapping community discovery method based on the similarity aggregation of multi-triangular groups is suitable for TCMF networks. The use of multi-triangular technology greatly improves the accuracy of community division, and the community structure information of drug groups can be accurately discovered from TCMF networks.

Description

technical field [0001] The invention relates to a method for excavating traditional Chinese medicine prescriptions, in particular to an overlapping community discovery method based on multi-triangular group similarity aggregation applicable to TCMF networks. Background technique [0002] Research on network community structure in complex network analysis has a long history, which involves various fields such as computer science, sociology, and life science. Analyzing the community structure in the network is very important for analyzing the network structure and understanding the characteristics of the network. There are many real complex networks in the real world, such as social networks, interlinking networks between Internet pages, literature citation networks, biological networks (such as protein interaction networks), paper co-authoring networks, and so on. Different real network structures represent the practical significance of their research directions. The Traditi...

AI Technical Summary

Problems solved by technology

Among them, the complexity of finding the initial community stage in this method is high, and the accuracy of the community discovery of traditional Chinese medicine groups in the TCMF network needs to be improved.

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