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Cross-social network user identification method based on community structure

A technology for user identification and social networking, applied in network data retrieval, neural learning methods, biological neural network models, etc., can solve problems such as limited network features and achieve the effect of improving accuracy

Active Publication Date: 2021-12-03
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, only considering the adjacent structure of nodes, the extracted network features are very limited.

Method used

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  • Cross-social network user identification method based on community structure
  • Cross-social network user identification method based on community structure
  • Cross-social network user identification method based on community structure

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Experimental program
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Embodiment Construction

[0059] The present invention will be further explained below in conjunction with accompanying drawing and specific embodiment:

[0060] 1. Definition of terms

[0061] The research object of the present invention is an undirected and unweighted graph, so the social network is expressed as G=(V, E), where V is the set of user nodes in the social network, and E is the set of user connections in the social network. Since the present invention takes two social networks as examples, so use G s =(V s ,E s ) represents the source network (Source Network), with G t =(V t ,E t ) represents the target network (Target Network).

[0062] source network G s As an example, Table 1 summarizes the representation method in the present invention, the target network G t means similar. Other symbols or definitions are interpreted later when they first appear.

[0063] Table 1: Symbol representation

[0064]

[0065] For the convenience of description, the following definitions are g...

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Abstract

The invention belongs to the technical field of social network user identification, and discloses a cross-social network user identity identification method based on community structure, comprising: step a, using network embedding to respectively map the source network and the target network to a low-dimensional vector space; step b. Based on the vector space, train the BP neural network in a supervised manner to obtain a BP neural network model that maps from the source network to the target network, and perform the identity verification of the source network user in the target network through the BP neural network model identify. In the process of learning the feature vector representation of the social network nodes, the present invention integrates the proximity features of the nodes and the community structure features, retains the structural features of the social network to the greatest extent, and improves the accuracy of user identification.

Description

technical field [0001] The invention belongs to the technical field of social network user identification, in particular to a cross-social network user identification method based on community structure. Background technique [0002] With the rapid development of the Internet and the gradual popularization of mobile devices, online social networks have become more and more popular, bringing great convenience to communication between people. Different social networks provide different types of services. People usually join different social networks according to the needs of work and life. Social networks have become a bridge connecting virtual cyberspace and the real physical world. For example, people usually share their current geographic location with friends on Foursquare; share pictures or articles on Twitter or Facebook. Therefore, generally, each user has accounts in multiple different social networks, but these accounts are often independent of each other. [0003] ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/901G06F16/958G06N3/04G06N3/08G06Q50/00
CPCG06F16/9024G06F16/958G06N3/084G06Q50/01G06N3/044
Inventor 刘琰郭晓宇左青松王煦中赵媛李永林
Owner PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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