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

Inactive Publication Date: 2017-02-22
BEIJING QIHOO TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the large number and variety of applications on the Internet at present, the classification standards of labels vary, and the labels corresponding to each application are not completely accurate. For example, an application with a lifestyle label may actually be an entertainment application. As a result, the accuracy of the recommendation results is poor, and it is difficult to meet the needs of users.

Method used

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  • Application recommendation method and system
  • Application recommendation method and system
  • Application recommendation method and system

Examples

Experimental program
Comparison scheme
Effect test

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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Abstract

The invention discloses an application recommendation method and system. The method comprises the following steps of: determining first attribute information of a user according to history behavior information, for applications, of the user; respectively determining an application preference relevance score between at least one history application indicated by the history behavior information and each to-be-recommended application, and respectively determining a first relevance score, a second relevance score and a third relevance score between the user and each to-be-recommended application according to set application theme information, set application label information and set application category information; determining a sorting score of each to-be-recommended application according to the application preference relevance score, the first relevance score, the second relevance score and the third relevance score; and pushing each to-be-recommended application according to the sorting score. Through the method and system disclosed by the invention, the problem that the application recommendation correctness is bad is solved.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to an application recommendation method and system. Background technique [0002] The Internet is an important way for people to obtain information. The main feature of the traditional Internet is that when users are looking for things they are interested in, they need to do a lot of searching and browsing operations, and they also need to manually filter the search and browsing results. In the end, the results that meet the requirements can be obtained. The entire acquisition process is cumbersome and consumes a lot of time and energy. [0003] This is especially true for the acquisition of applications. At present, there are already some websites that analyze the label information of the application, and then recommend the application according to the label information of the application. However, due to the large number and variety of applications on the Internet at presen...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 唐竞胜曹国栋王振凯
Owner BEIJING QIHOO TECH CO LTD
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