Application recommendation method and device

A technology for application recommendation and various applications, applied in special data processing applications, instruments, network data retrieval, etc., can solve the problems of insufficient recommendation effect, long time consumption, affecting the accuracy of application recommendation, etc., to avoid human intervention. Effect

Inactive Publication Date: 2015-04-08
CHINA UNITED NETWORK COMM GRP CO LTD
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AI Technical Summary

Problems solved by technology

Although application recommendations can be provided to users based on information such as the number of downloads and user reviews of the application, human intervention often exists in the ranking of download times and user reviews, which affects the effect of recommending applications to users.
In addition, for each user, the business he is interested in does not necessarily match the number of downloads and user reviews, which obviously will make the application recommendation effect worse.
Since the recommendation effect does not meet the user's requirements, users often need to query and browse a large number of applications according to their own interests and needs in order to obtain the applicati...

Method used

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  • Application recommendation method and device

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Embodiment Construction

[0043] In order to make the purpose, technical solution and advantages of the application clearer, the embodiments of the application will be described in detail below in conjunction with the accompanying drawings. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined arbitrarily with each other.

[0044] figure 1 A flow chart of the method recommended for the implementation of the application of the present invention, such as figure 1 shown, including:

[0045] Step 100, obtaining the online records of all users within a preset time period, and counting the access information of each user's access to the application.

[0046] Table 1 is the online records of some users obtained from the existing database. As shown in Table 1, the online records are routinely counted according to different users and applications, and the corresponding visits including the access of each user to each...

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Abstract

The invention discloses an application recommendation method and device. The method comprises obtaining all user web surfing records in preset time, and calculating access information of all user access applications; sorting all user access information on account of all applications and calculating all user application access interest scores based on preset sorting scoring rules; analyzing all application access interest scores of all users to obtain user categories and the similarity among all users in the user categories, and performing application recommendation based on the similarity among the users. By means of the method and the device, the access information is analyzed to obtain the interest scores of the users towards the applications, the similarity among the users is obtained through the application access interest scores of the users, and the application recommendation is achieved through the similarity between the interest scores and the users, accordingly, application recommendation is achieved, human interventions in application recommendation are prevented, and recommendation of applications interested by users is achieved.

Description

technical field [0001] This application relates to mobile Internet application technology, in particular to a method and device for implementing application recommendation based on user surfing behavior. Background technique [0002] With the rapid development of the mobile Internet, mobile terminal applications are becoming more and more abundant. According to statistics, the number of applications in the Apple App Store has reached one million, and Android applications are growing faster, most of which are web-based applications. [0003] At present, the application store mainly recommends applications to users based on the number of application downloads and user reviews. Although application recommendations can be provided to users based on information such as the number of downloads and user reviews of applications, human intervention often exists in the ranking of download times and user reviews, which affects the effect of recommending applications to users. In addit...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535G06F16/951
Inventor 肖吉李希金
Owner CHINA UNITED NETWORK COMM GRP CO LTD
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