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Method for detecting cohesion subgraphs in symbolic network based on k truss and balance theory

A technology of symbolic networks and symbolic graphs, applied in data processing applications, special data processing applications, instruments, etc., to achieve strong robustness, large benefits, and reduced search space

Pending Publication Date: 2021-01-22
ZHEJIANG GONGSHANG UNIVERSITY
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  • Claims
  • Application Information

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Problems solved by technology

However, there is currently no model that satisfies both the density constraint and the balance constraint well

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  • Method for detecting cohesion subgraphs in symbolic network based on k truss and balance theory
  • Method for detecting cohesion subgraphs in symbolic network based on k truss and balance theory
  • Method for detecting cohesion subgraphs in symbolic network based on k truss and balance theory

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Embodiment Construction

[0035] In order to make the above objects, features and advantages of the present invention more comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0036] In the following description, a lot of specific details are set forth in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those described here, and those skilled in the art can do it without departing from the meaning of the present invention. By analogy, the present invention is therefore not limited to the specific examples disclosed below.

[0037] This application proposes a method for detecting cohesive subgraphs in symbolic networks based on k-truss and balance theory, which includes three novel pruning strategies and an efficient maximally signed k-truss detection algorithm (SKT algorithm for short). The implementation process of each part is d...

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Abstract

The invention discloses a method for detecting cohesion subgraphs in a symbolic network based on a k truss and a balance theory. In order to find a group meeting density constraint and balance constraint at the same time, the invention provides a new cohesion sub-graph model on a symbolic network, i.e., a maximum symbol k truss, which meets three conditions: any one edge is contained in at least (k-2) triangles; any unbalanced triangle is not included; that is to say, any hypergraph is not provided with a symbol k truss. Considering the attributes of the balance triangle and the k truss, the invention provides a new pruning strategy, so that the search space is reduced more effectively. Meanwhile, an efficient SKT algorithm is developed in combination with a new pruning strategy, so that amaximum signed k truss can be quickly found in a large signed network. The application of the method provided by the invention has great benefits on the detection of the cohesion subgraph and the identification of the trust community.

Description

technical field [0001] The invention belongs to the technical field of multimedia data detection, in particular to a method for detecting cohesive subgraphs in symbolic networks based on k-truss and balance theory. Background technique [0002] With the rapid development of Internet and World Wide Web technologies, social networks such as Facebook and Twitter have become more and more popular in recent years. There is growing research interest in social networks, and many efforts have been made to detect cohesive subgraphs. Many cohesive subgraph models have been proposed in current research, such as k-core, k-truss and k-cluster. Most existing research on cohesive subgraph detection focuses on unsigned graphs, which regard all connections between users as positive relations. However, social interactions involve both positive relationships (such as friends) and negative relationships (such as enemies). Ignoring negative information from edges may fail to properly characte...

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Application Information

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IPC IPC(8): G06F16/901G06Q50/00
CPCG06Q50/01G06F16/9024
Inventor 王潇杨孙仁杰赵俊吴艳萍朱秋雨陈晨
Owner ZHEJIANG GONGSHANG UNIVERSITY
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