A community detection method and device for heterogeneous dynamic information network

Abstract

The invention proposes a community detection method and device for a heterogeneous dynamic information network, which performs community detection on a dynamic heterogeneous information network constructed from data crawled from the network. The device includes a dynamic network generation module, a basic network community detection module, a dynamic community detection module and an increment-based community structure update module. The method includes: establishing a basic network and an incremental sequence for the research data, the basic network is a multi-channel network, detecting the community structure for each layer of the network, and then constructing a consensus graph to detect the community structure in the consensus graph; adding and deleting nodes, The community structure update strategy is set for the four incremental types of edge generation and edge disappearance, and the community structure is updated according to the update strategy for the incremental sequence generated in the network. The invention fully considers various possible increment types and community evolution conditions that may be caused by different types of increments, and can accurately detect the current community structure of the network.

Description

Technical field[0001]The present invention belongs to the field of network data processing, and in particular, the present invention relates to a method and apparatus for community detection on a heterogeneous dynamic information network.Background technique[0002]There are many complex networks in the real world, such as Internet, interpersonal networks, disease communication networks, and scientists cooperation networks. A large number of studies have shown that community structure is an important feature of complex networks, and nodes are closely linked in the community and less connection between communities. Community structure plays an increasingly important role in complex networks. It can help us understand the functions of complex networks, find potential laws, and predict the behavior of complex networks. For example, the community structure represents a group with the same hobbies in the social network; the web page has more links in the same community; in the literature n...

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Problems solved by technology

[0013] In view of the imperfect incremental processing in the existing community detection methods, there is a problem of long-term community consistency, and the existing incremental community detection methods are all aimed at homogeneous dynamic information networks and cannot be applied to heterogeneous dynamic information networks. The invention provides a community detection method and device for heterogeneous dynamic information networks, based on incremental thinking to deal with the influence of network dynamic changes on community structures, and supports heterogeneous dynamic information networks by constructing multi-way networks and consistent graphs community detection

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