Complex network community structure mining method based on triangular cluster multi-label transmission

A complex network and community mining technology, applied in the field of complex networks, can solve problems such as poor robustness, low detection accuracy, and inability to detect overlapping community structures

Active Publication Date: 2013-04-03
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

However, the robustness of this method is poor, the detection accuracy is not high, and it cannot detect community structures with overlapping

Method used

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  • Complex network community structure mining method based on triangular cluster multi-label transmission
  • Complex network community structure mining method based on triangular cluster multi-label transmission
  • Complex network community structure mining method based on triangular cluster multi-label transmission

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Embodiment Construction

[0065] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0066] This embodiment adopts the Zachary karate club network, a classic data set in social networks, which contains 34 nodes and 78 edges. The specific steps are as follows:

[0067] ① Assign an empty label to each node of the karate club network to be tested;

[0068] ②Calculate the triangular cluster coefficient TC(e ij ):

[0069] TC(e ij )=|N(v i )∩N(v j )|

[0070] Among them: N(v i ) is node v i The set of neighbor nodes, ∩ is an operator for intersection, |·| is an operator for set base, i is 1, 2, 3, ..., N;

[0071] ③ Search out the side with the largest triangular cluster coefficient;

[0072]...

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Abstract

The invention discloses a complex network community structure mining method based on triangular cluster multi-label transmission, which includes the steps of: searching the mutually disjointed triangular clusters in the network; setting different labels for the nodes of different triangular clusters to be used as an initial state for the transmission of the labels; synchronously updating the transmission of the labels of all the nodes in the network according to a multi-label renewal rule; comparing the updated label sets with the previously updated label sets; continuing to update the transmission of the labels if the labels are still being transmitted; if the labels oscillate, eliminating the oscillation and then continuing to update; if the labels no longer change again, stopping updating to obtain the overlapped community structures in the network. The complex network community structure mining method is lower in time complexity and is applicable for large-scale complex networks. In addition, the method can well detect the overlapped sections of the network community structures, has good robustness and is higher in detection accuracy.

Description

technical field [0001] The invention relates to a method in the field of complex networks, in particular to a method for mining complex network community structures based on triangular cluster multi-label propagation. Background technique [0002] A complex network is an abstract representation of complex systems in the real world. The nodes in a complex network represent the individuals in the complex system, and the connections between nodes represent the natural or man-made connections between individuals in the system according to certain rules. relationship. At present, complex networks have been widely used to represent various complex systems such as power networks, communication networks, the Internet, and social networks. [0003] Community structure is an important topological characteristic of complex networks. The entire complex network is composed of several community structures. The nodes within each community structure are very tightly connected, while the co...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 李生红赵郁忻张爱新刘超
Owner SHANGHAI JIAO TONG UNIV
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