A community detection method for symbolic networks based on oscillator phase synchronization
A symbol network and detection method technology, applied in the network field, can solve the problems of complex calculation process, reduced detection efficiency, long time consumption, etc., to achieve the effect of reducing complexity, improving detection efficiency, and overcoming long calculation time
Inactive Publication Date: 2016-05-25
XIDIAN UNIV
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The disadvantage of this method is that this method is not suitable for community detection of symbolic networks with negative relationships
For a given network, every time the initial community module is merged, it is necessary to find the proximity of the initial community neighbor nodes, and then calculate the Q value of the community module obtained by merging the initial community module. The patent calculation process is too complicated and takes a long time to calculate The proximity of the nodes, the number of cycles is too much, which reduces the detection efficiency and takes a long time
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[0037] The present invention will be described in further detail below in conjunction with the figures.
[0038] Refer to attached figure 1 , the steps of the present invention are as follows:
[0039]Step 1. Generate an adjacency matrix.
[0040] The nodes in the symbolic network to be detected are numbered sequentially from 1 to N, and N represents the total number of nodes in the symbolic network; the adjacency matrix corresponding to the forward connection edge between node i and node j in the symbolic network to be detected element of a ij Set to 1; set the element a in the adjacency matrix corresponding to the unconnected edge between node i and node j in the symbolic network to be detected ij Set to 0; the element a in the adjacency matrix corresponding to the negative connection edge between node i and node j in the symbolic network to be detected ij Set to -1; obtain the adjacency matrix corresponding to the symbol network to be detected. The value range of N is ...
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The invention provides a symbol network community detecting method based on oscillator phase synchronization, overcoming the defects that the prior art is not suitable for symbol network community detection, low in detection efficiency and relatively high in complexity. The symbol network community detecting method is realized through the steps of (1) generating an adjacent matrix; (2) initiating a node phase; (3) updating the node phase; (4) judging whether the updated node phase is stable; (5) counting the number of nodes among all subintervals; (6) detecting the community and overlapped nodes of a symbol network; (7) outputting a detected result. The method provided by the invention can be used for realizing the community detection for the symbol network by using an improved oscillator model based on an oscillator phase synchronization theory, effectively increasing the node phase synchronization efficiency in a concurrent processing way of a differential equation, lowering the complexity of the community detection for the symbol network and effectively detecting the community structure and overlapped nodes of the symbol network.
Description
technical field [0001] The invention belongs to the field of network technology, and further relates to a symbolic network community detection method based on oscillator phase synchronization in the field of data mining technology. The invention introduces an improved oscillator model and utilizes the phase synchronization principle of the oscillator to improve the parallel processing capability, and can quickly and effectively detect each community of the symbol network. Background technique [0002] At present, complex networks have become one of the most cutting-edge and challenging multidisciplinary research fields. The existing complex network analysis often uses a single positive relationship boundary value model to represent the relationship between nodes. However, in the real social network relationship, for a thing The evaluation or the relationship between people often has two sides, support and opposition, friends and enemies, positive and negative, and this netwo...
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IPC IPC(8): H04L12/26
Inventor 吴建设焦李成张龙缑水平焦洋王芳郭开武袁林侯艳巧
Owner XIDIAN UNIV