Personalized information association method and device for cold start user and storage medium

Abstract

The embodiment of the invention provides a personalized information association method and device for a cold start user and a computer readable storage medium. The personalized information associationmethod for the cold start user comprises the steps of obtaining personalized information of an application page corresponding to an installation instruction in response to the installation instruction from a user terminal; writing the personalized information into an application installation file corresponding to the installation instruction; and sending the application installation file to the user terminal, wherein the application installation file is used for indicating that the personalized information is used as the associated information of the cold start user after the application corresponding to the installation instruction is installed. According to the embodiment of the invention, the personalized information is written into the application installation file corresponding to the installation instruction. The data association between the page before the application is installed and the application after the application is installed is realized, so that the application can obtain the personalized information of the cold boot user according to the information carried in the application installation file to provide corresponding personalized services, and the user experience is improved.

Description

technical field [0001] The present invention relates to the field of information technology, in particular to a method and device for associating personalized information of a cold-start user, and a computer-readable storage medium. Background technique [0002] As the number and types of services in the network continue to increase, in order to help users find the desired service among a large number of services, service recommendation technology emerges as the times require. Most of the traditional service recommendation methods are based on the target user's historical service records, looking for neighbor users with similar behaviors to the target user, and then recommending the services used by the neighbor users, or looking for services similar to the target user's used services for recommendation. However, these methods cannot be recommended for users who have no service usage records, that is, cold-start users. Therefore, it is difficult to obtain personalized infor...

AI Technical Summary

Problems solved by technology

The newly installed APP cannot distinguish the source of the installation package download, and cannot realize the association of accurate recommendation information for the downloaded APK

[0004] To sum up, data association cannot be realized between the web page before APP installation and the APP after installation, and the APP cannot obtain the personalized information of cold-start users, and cannot provide corresponding personalized services, resulting in poor user experience.

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