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Cross-social-network user identity recognition 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: 2019-12-03
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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 identity recognition method based on community structure
  • Cross-social-network user identity recognition method based on community structure
  • Cross-social-network user identity recognition method based on community structure

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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 collection of user nodes in the social network, and E is the collection 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 def...

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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 a community structure, which comprises the following steps: step a, respectively mapping a source network and a target network to a low-dimensional vector space by adopting a network embedding mode; and step b, based on the vector space, training a BP neural network in a supervised manner to obtain a BP neural network model for realizing mapping from a source network to a target network, and identifying the user identity of the source network in the target network through the BP neural network model. In the process of learning the feature vector representation of the social network nodes, the proximity features and the community structure features of the nodes are fused, the structure features of the social network are reserved to the maximum extent, and the user identity recognition accuracy is improved.

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 Applications(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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