Application recommendation method and application recommendation system

A technology for application recommendation and user application in the network field, which can solve problems such as limited relevant information, a large number of system resources, and difficulty in finding videos, and achieve the effect of increasing accuracy, reducing occupation, and simplifying the steps of recommendation

Inactive Publication Date: 2013-07-10
BEIJING IZP NETWORK TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0009] When using the content filtering method, it is difficult to find videos that can be recommended due to the limited information of some videos; the collaborative filtering method does not need to judge based on the relevant information of the video, and can solve these problems of the content filtering method. The collaborative filtering method ...

Method used

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

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Embodiment Construction

[0063] In order to make the above objects, features and advantages of the present application more obvious and comprehensible, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0064] When a website provides a personalized recommendation service, it needs to analyze and mine the current user's access behavior, and recommend some interesting applications to the user through the results of data mining, so as to improve the user's viewing rate on the website. Commonly used recommendation methods include content-based filtering methods and collaborative filtering methods.

[0065] The content-based filtering method is based on the relevance of files to recommend, which is an extension of the content information contained in the access data. Specifically, user preferences are constructed according to the current user's historical information (such as evaluation, sharing, and favorite...

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Abstract

The invention provides an application recommendation method and an application recommendation system. The application recommendation method includes the following steps: access behavior data of multiple reference users to preset multiple applications are obtained, the multiple reference users are subjected to grouping according to the access behavior data, and each of the multiple applications has a corresponding application class; a group which a target user belongs to is determined according to access behavior data of the target user to the multiple applications, access weighted values of the target user to different application classes are subjected to statistics, and the application classes with the access weighted values which are in a preset range are regarded as interest application classes; and the applications which belong to the interest application classes are extracted from the multiple applications which are accessed by all the reference users and are in the group which the target user belongs to, and then the applications are recommended to the target user. The application recommendation method and the application recommendation system can occupy fewer system resources when the applications are recommended.

Description

technical field [0001] The present application relates to the field of network technologies, and in particular to an application recommendation method and an application recommendation device. Background technique [0002] With the continuous increase of people's demand for network applications, personalized recommendation services have gradually entered people's lives. Personalized recommendation services refer to targeted recommendations for different visitors. At present, many emerging websites use personalized recommendation services to attract consumers to browse. Specifically, through the analysis of each visitor's visit behavior, personalized recommendations are given to visitors according to the analysis results. [0003] At present, the more commonly used recommendation methods mainly include the following two types: [0004] 1. Content-Based Filtering (CB, Content-Based Filtering) [0005] This method is based on the access data of the target user (that is, the o...

Claims

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Application Information

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IPC IPC(8): G06Q30/02
Inventor 郑巍罗峰黄苏支李娜
Owner BEIJING IZP NETWORK TECH CO LTD
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