Target user prediction method and device, background server and storage medium

Abstract

The embodiment of the invention provides a target user prediction method and device, a background server and a storage medium. The method comprises the steps of determining user characteristics of a to-be-tested user, wherein the user characteristics at least comprise user portrait data of the to-be-tested user, behavior characteristics of the to-be-tested user and friends in each first type application of a plurality of first type applications, and behavior characteristics of the to-be-tested user in at least one non-first type application; generating prediction features of the to-be-tested user according to the user features of the to-be-tested user and the application features of the target first type application; and inputting the prediction features of the user to be tested into a pre-constructed target user prediction model, and predicting through the target user prediction model to obtain the probability that the user to be tested is a target user of the target first type application. According to the embodiment of the invention, the prediction accuracy of the target user can be improved, and the timely prediction of the target user and the prediction of the target users ofdifferent first type applications are realized.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to a target user prediction method, device, background server and storage medium. Background technique [0002] The prediction of lost users and potential users of applications (such as games, online shopping, etc.) is of great significance for prolonging the life cycle of applications. Among them, the lost users of the application refer to the users who have used the application before, but no longer use the application due to reasons such as losing interest in the application; predicting the lost users of the application can reasonably plan the operation of the application to retain the users who are about to lose , to extend the life cycle of the application. Potential users of the application refer to users who have never used the application but may be interested in the application; predicting the potential users of the application can make accurate application...

AI Technical Summary

Problems solved by technology

However, the target user prediction method of the current application uses a single factor to determine the target user of the application, and there is a problem that the prediction accuracy of the target user of the application is low; therefore, how to improve the target user prediction method of the application to improve the target user of the application The user's prediction accuracy has become a problem that those skilled in the art need to consider

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