Application recommendation method and system
A technology for application recommendation and label application, applied in the Internet field, can solve problems such as poor accuracy of recommendation results, difficulty in meeting user needs, and uneven label classification standards, so as to achieve the effect of improving accuracy
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Embodiment 1
[0070] refer to figure 1 , shows a flowchart of steps of an application recommendation method in Embodiment 1 of the present invention. In this embodiment, the application recommendation method may include:
[0071] Step 102: Determine the first attribute information of the user according to the historical behavior information of the user on the application.
[0072] In this embodiment, the user's historical behavior information on applications includes, but is not limited to: at least one historical application visited by the user. Wherein, the at least one historical application visited may be, but not limited to: an application browsed, searched, clicked, or downloaded by the user.
[0073] The first attribute information may at least include: set application theme information, set application tag information, and set application category information. Wherein, the set application theme information, set application tag information and set application category information ...
Embodiment 2
[0087] refer to figure 2 , shows a flowchart of steps of an application recommendation method in Embodiment 2 of the present invention. In this embodiment, the application recommendation method can be implemented based on but not limited to an application platform, and the application platform can be applied to smart devices such as mobile terminals, PCs (Personal computers, personal computers), and Pads (Portable android devices, tablet computers). in the terminal device.
[0088] Wherein, the application recommendation method may include:
[0089] Step 202: Determine the first attribute information of the user according to the historical behavior information of the user on the application.
[0090] In this embodiment, the historical behavior information may include: at least one historical application accessed by the user. The first attribute information may include: set application theme information, set application tag information, and set application category informat...
Embodiment 3
[0123] In combination with the foregoing embodiments, the application recommendation method for user A is described in detail by taking the application recommendation process for user A as an example.
[0124] refer to image 3 , shows a step diagram of the application recommendation process for user A in Embodiment 3 of the present invention. In this embodiment, the application recommendation process for user A may be as follows:
[0125] In step 302, historical behavior information of user A is acquired through log information.
[0126] In this embodiment, the historical behavior information of user A may at least include: historical applications accessed by user A, and the number of times user A visits each historical application. It should be noted that the access includes but is not limited to: click, browse, search and so on.
[0127] In this embodiment, the historical applications visited by user A and the number of visits may be shown in Table 1 below:
[0128] ...
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