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
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[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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