Cross-social-network user identity recognition method based on neural tensor network

Abstract

The invention provides a cross-social-network user identity recognition method based on a neural tensor network. The method comprises the following steps: step 1, based on network representation learning of Random Walks and Skipgram models, mapping network structure spaces of a source network Gs and a target network Gt to vector spaces respectively; step 2, based on the vector space obtained in the step 1, modeling an association relationship between the user nodes in the source network Gs and the target network Gt by using a neural tensor network model; and 3, inputting the incidence relationvector obtained by modeling in the step 2 into a multi-layer perceptron model for dichotomy, and judging whether the user node pairs between the source network Gs and the target network Gt point to the same real user or not according to a classification result. According to the method, the neural tensor network model is adopted to replace a standard neural network model, the model has stronger capability of expressing the relationship among cross-network users, and two user vectors can be associated in multiple dimensions.

Description

technical field [0001] The invention relates to the technical field of identification, in particular to a neural tensor network-based cross-social network user identification method. 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, which brings great convenience to the communication between people. Different social networks provide different types of services, and people usually join different social networks according to the needs of work and life. Each user usually has accounts in different social networks, but accounts belonging to the same person are often isolated from each other and have little connection with each other. A typical goal of the cross-social network user identification problem is to detect whether accounts from different social networks belong to the same natural person in the real world, also known as account association, ...

AI Technical Summary

Problems solved by technology

[0007] Aiming at the problem that existing user identification algorithms usually use linear models or standard neural network layers to measure the similarity between cross-social network users and can hardly model the implicit relationship between them, the present invention provides a method based on Cross-social network user identification method based on neural tensor network

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