Training method of social networking account mapping model, mapping method and system

Abstract

The present invention provides a training method of a social networking account mapping model. The method comprises: 1) combining any one account in a microblog account set s known in a mapping relationship and any one account in a microblog account set t known in the mapping relationship to form a training set; 2) extracting from each account combination an account combination feature vector comprising: respective text features of two accounts in the account combination, social networking relation features of the two accounts in the microblogs to which the two accounts pertain, and extended common neighbor features of the two accounts, wherein an extended common neighbor is a neighbor account pair pertaining to the same individual known in the respective neighbor accounts of the two accounts; 3) training based on the machine learning technology to obtain a social networking account mapping model. The present invention further provides a corresponding social networking account mapping method and system. According to the present invention, adverse impacts caused by sparsity of relationship data are reduced, and accuracy of social networking account mapping is effectively improved.

Description

technical field [0001] The present invention relates to the field of social computing, in particular, the present invention relates to a social network account mapping method and system. Background technique [0002] Nowadays, more and more people use social networks around the world, and people usually carry out social behaviors such as posting information and contacting others through multiple social networks. In different social networks, multiple accounts belonging to the same user are mostly isolated from each other, and generally there is no connection between them. However, these social networks do not have a unified organization or cooperation to connect data, thus making it difficult to obtain a set of accounts belonging to the same user. If the collection of accounts belonging to the same user in different social networks can be obtained, more valuable services can be provided in aspects such as link recommendation and community analysis based on multiple social n...

AI Technical Summary

Problems solved by technology

However, if the existing account mapping scheme is directly used for account alignment across social networks, its accuracy and mapping probability are insufficient.

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