A sequential smooth community partitioning method and device based on label diffusion

Abstract

The invention discloses a sequential smooth community partitioning method based on label diffusion. The method comprises the following steps: 1) obtaining label values of each node in the network to be partitioned at the preceding time of the current time; 2) judging whether that oscillation numb is greater than a preset threshold value; 3), if not, acquiring the first preference weight value of the node, taking the first preference value as the current preference value of the node; 4) if yes, acquiring a second preference weight value of the node, taking the second preference value as the current preference value of the node; 5) updating that label value of the node at the current time and returning to execute the step 2) until each node in the to-be-divided network is grouped into a community composed of nodes with identical label values. The embodiment of the invention also provides a timing smoothing community dividing device based on label diffusion. By applying the embodiment ofthe invention, the accuracy of community dividing can be improved.

Description

technical field [0001] The present invention relates to a community division method and device, and more particularly to a time-series smooth community division method and device based on label diffusion. Background technique [0002] There are a large number of complex network systems in the real world, such as the Internet, social networks, scientists' cooperation networks, communication networks, protein interaction networks, gene regulation networks, etc. In a complex network, the relationships among the individual constituents of the network are different. Therefore, there is a phenomenon of closeness and distance between individuals. Therefore, the complex network will be divided into communities with boundaries. The interrelationships between individuals in the network can be studied. The community structure describes a kind of heterogeneous connection characteristics in the network, that is, the network is composed of different node clusters, the nodes in the cluste...

AI Technical Summary

Problems solved by technology

[0004] However, in the existing label propagation algorithm, randomness is introduced from two aspects: when updating the label value, when there are multiple label values ​​that meet the conditions, one is randomly selected; and the update order of the nodes is also performed randomly. , therefore, the community division results produced by the existing technology will have large differences in timing, which in turn makes the algorithm less robust and stable

Therefore, the existing technology has the technical problem of inaccurate dynamic community division results

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