Hybrid clustering method aiming at complicated network

Abstract

The invention provides a hybrid clustering method aiming at a complicated network, and belongs to the field of data mining of a community network. The method comprises the following steps of: partitioning the complicated network by a heuristic clustering method, and setting an optimization terminating function and an iterative terminating threshold value to obtain a relatively good network community division result; combining the networks by an optimization-based clustering method, and storing an optimal network community division result by calculating a final optimization terminating function; and finally outputting a community structure. By the method, a large-scale complicated network can be subjected to community division or clustering, so that a community division result is good; furthermore, the Girvan-Newman (GN) algorithm precision based on connection clustering coefficients is improved, and the time loss is avoided; and high user experience can be guaranteed.

Description

technical field [0001] The invention belongs to the field of data mining of community networks, and relates to a hybrid clustering method for complex networks. Background technique [0002] Since the 1990s, the rapid development of information technology represented by the Internet has brought human society into the network era. From the Internet to the WWW, from the food chain network in the ecological environment to the metabolic network in the organism, from the scientific research cooperation network to various political, economic and social networks, from the large-scale power network to the global transportation network, people live in a world full of various In a world of various complex networks. With the discovery of the small-world effect and scale-free properties in real-world networks, there has been an upsurge in the study of complex networks. Complex networks have strong interdisciplinary features, and the research on complex networks involves graph theory, s...

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Problems solved by technology

[0017] The method of the present invention aims at the problem that the improved GN algorithm reduces the accuracy of clustering results while increasing the speed when clustering complex networks, and proposes a hybrid clustering method for complex networks, which is especially suitable for online Social network, telephone network in communication system, etc.

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