Cross-social media account matching approach that integrates social relationships and naming features
A social relationship and social media technology, applied in the field of cross-social media account matching, can solve the problems of inability to promote social media account matching, poor generalization ability of classification models, large randomness of negative example data, etc., and achieve enhanced model generalization ability , improve accuracy and generalization ability, and improve efficiency
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[0027] The present invention proposes a user association matching method that integrates social relations and naming features. The method utilizes the user relationship network to narrow down the range of pre-matched users, and reduces the calculation amount in the account matching process; and the training set construction of the existing method is not ideal enough In order to solve the problem, it is proposed to add samples that are easily misclassified each time into the training set through iterative training to increase the proportion of samples that are at the boundary of the classifier. At the same time, combined with the method of ensemble learning, it can accurately and efficiently complete cross-social media user Accounts match. The process is generally divided into two parts, potential associated user pair generation and user association result determination. Potentially associated user pair generation Find out which accounts need to be associated and judged, we can...
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