The invention provides an APP pushing method and device. The method comprises: acquiring historical APP downloading data of the user and APP access data of the user in a second preset period, whereinthe historical APP downloading data comprises APP downloading data in a first preset period and APP downloading data before the first preset period, and the first preset period is greater than the second preset period; determining a user type according to the historical downloading APP data and the access APP data; and determining whether to push the target APP to the user or not according to theuser type, thereby realizing accurate popularization of the APP.

APP pushing method and device

The invention relates to a tourism product recommendation method and device, computer equipment and a storage medium. The method comprises the steps that login information of a target user in a tourism product website is acquired, and identity identification information of the target user is acquired according to the login information; Determining the user type of the target user in the tourism product website according to the identity identification information; When the target user is the first type of user, displaying a preset evaluation interface which at least comprises a plurality of evaluation questions; And obtaining reply data of the target user to the evaluation question, determining a first target recommendation list according to the reply data, and recommending the tourism product to the target user according to the first target recommendation list. By adopting the method, the matching degree of the recommended tourism products and user requirements can be improved.

Tourism product recommendation method and device, computer equipment and storage medium

An application recommendation method and a terminal are provided according to an embodiment of the present invention By obtaining the browsing behavior of an in-application download site within a userthreshold time, determining an interest tag of a user according to the browsing behavior, calculating an interest degree for each application in a multi-application download website according to theinterest tag, and recommending application to users according to the interest degree, the problem that the off-line recommendation engine cannot handle the real-time search behavior; as the supplementof the search engine, the method can calculate the user interest tag more accurately and timely, provide the real-time personalized recommendation service for the user, improve the user experience can be improved, and improve the download conversion rate.

An application recommendation method and a terminal

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An application recommendation method and a terminal