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Application recommendation method and device

A technology for application recommendation and user, applied in data processing applications, special data processing applications, instruments, etc., can solve the problems of reducing user experience, negative impact of recommendation accuracy, single consideration factors, etc., to achieve an increased recommendation success rate, high accuracy The effect of sexual referrals

Inactive Publication Date: 2017-10-31
CHINA MOBILE GRP GUANGDONG CO LTD
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0004] The existing model only considers the information of the user's installed or used applications, and the consideration is too single. It only considers the factor of "product" and does not consider the factor of the user's actual needs. The recommended applications to the user cannot meet the user's needs. Due to actual needs, users will not use the recommended applications, reducing user experience, and thus negatively affecting the accuracy of recommendations

Method used

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  • Application recommendation method and device

Examples

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Comparison scheme
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Embodiment 1

[0066] An embodiment of the present invention provides an application recommendation method, which is applied to an application recommendation device, which may be a part of the server or a separate device, such as figure 1 As shown, the method includes:

[0067] Step 101. Obtain the user's application preference score and user information.

[0068] Here, when acquiring the user's application preference score, the entropy method is used, which is very mature in practical applications, and will not be described in detail in this embodiment. The purpose of obtaining user information is to prepare for the next steps. Wherein, the user information can be obtained directly from the server.

[0069] Specifically, obtaining the user's application preference score may be performed in the following small steps.

[0070] (1) Initialize the user-application preference score matrix

[0071] First, define the user-app preference matrix: where g ij Indicates the preference score of t...

Embodiment 2

[0156] An application recommendation device 20 provided by an embodiment of the present invention, such as Figure 5 As shown, the device 20 includes:

[0157] Obtaining module 201, for obtaining user's application preference score and user information;

[0158] A determining module 202, configured to determine the comprehensive similarity between the users according to the user information;

[0159] The determining module is further configured to determine recommended applications according to the application preference score and the comprehensive similarity.

[0160] In this way, according to the application preference score of a certain user and the comprehensive similarity between the user and other users, the recommended application for the user can be determined efficiently and accurately. In this way, not only the user has installed or used It also considers the comprehensive similarity between the user and other users, so as to achieve high-accuracy recommendation fo...

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Abstract

The embodiment of the invention discloses an application recommendation method.The method includes: acquiring application preference scores of users and user information; determining a comprehensive similarity degree between the users according to the user information; and determining recommended applications according to the application preference scores and the comprehensive similarity degree. The embodiment of the invention also discloses an application recommendation device at the same time.

Description

technical field [0001] The invention relates to data mining technology, in particular to an application recommendation method and device. Background technique [0002] With the rapid development of terminal applications, especially for the most frequently used mobile phones in daily life, users need to spend a lot of time to find the applications they want to install. In order to make it easier for users to find the applications they want to install, an application recommendation system emerges as the times require. Among them, the accuracy of the recommended application is an important indicator to measure the quality of the application recommendation system. [0003] In the prior art, taking mobile phones as an example, the mobile application recommendation mode is basically based on the factor of "product" (i.e. application). Specifically, data mining algorithm tools such as correlation analysis are used to explore the similarity and After the user chooses to install or...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q50/00
CPCG06F16/9535G06Q50/01
Inventor 张湛梅张晓川徐睿崔志顺
Owner CHINA MOBILE GRP GUANGDONG CO LTD
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