Local community digging method of complicated network

Abstract

The invention relates to the technical field of a network and particularly relates to a local community digging method of a complicated network, which can effectively identify a local community structure of the complicated network, has lower time complexity, and has fewer wrongly-divided nodes. The local community digging method comprises the following steps of: taking a maximum degree node in the network as a starting node and calculating a neighbored node to obtain a neighbored node set; finding out a node which has the most common neighbored nodes with the maximum degree node; forming an initial local community by the two node sets; obtaining each neighbored node proximity of the initial local community and adding the node with the maximum proximity into the initial local community to form a new initial local community; calculating a Q value of the initial local community; and repeating the steps until the Q value of the formed new initial local community is more than 0 or the node in the network is zero.

Description

technical field [0001] The invention relates to the field of network technology, in particular to a mining method for local communities in complex networks. Background technique [0002] In recent years, complex networks have been widely used, such as online social networks, scientists' cooperation networks, etc., but there is no precise and strict definition of complex networks. With the in-depth research on the physical meaning and mathematical characteristics of complex network properties, it is found that there are community structures in many actual networks, that is, the entire network is composed of several communities, and the connections between the internal nodes of each community are relatively close, but the connections between each community are relatively close. The connections between them are relatively sparse. Being able to quickly discover "communities" in large and complex networks has important practical application value. For example, communities in onl...

AI Technical Summary

Problems solved by technology

[0004] Recently, researchers have proposed a variety of local community discovery algorithms, such as a method for mining community structures based on Hub, which needs to know the number of network communities in advance, but it is difficult to know the number of network communities in advance in real networks; For example, the BB algorithm is a local method to find the community structure of a certain node. The defect of this algorithm is that it adds or excludes all the neighbor nodes in the community.

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