A method and device for predicting user off-grid

A user and off-grid technology, applied in the Internet field, can solve problems such as lack of interest, user dislike, and leaving

Active Publication Date: 2017-02-08
ALIBABA (CHINA) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But this method has a disadvantage. First, although it can be basically judged that the user has left the network, we cannot predict other behaviors of the user. For example, the user may have gone to other websites; It is no longer interested in the original browsing content; or the user leaves because he does not like a certain function of the website, these are also impossible to count
[0004] The chain-type mining method commonly used in the existing telecommunications industry to mine users' online behavior is only suitable for flat business structures and cannot satisfy the multi-dimensional operation methods of users of social networking sites

Method used

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  • A method and device for predicting user off-grid
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  • A method and device for predicting user off-grid

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0038] Example 1, see figure 1 , the present invention discloses a method for predicting user off-grid, comprising:

[0039] S1. Allocate the matrix site element table to the registered users who log in, and set the initial value of each element;

[0040] The matrix site element table of this embodiment includes horizontal columns and vertical columns, the horizontal column is user behavior classification, the user behavior classification includes: browsing, posting, commenting, sharing, deletion, the vertical column is at least one site function collection classification, site function classification Collection categories include: news, albums, logs, friends, BLOG.

[0041] The specific implementation method is first to set all operations of a social networking site as a user behavior matrix, the vertical column is classified by user behavior (browse, post, update), and the horizontal column is a collection of functions of the same nature of one or more sites as (new things ...

Embodiment 2

[0051] like Figure 4 As shown, the differences between this embodiment and Embodiment 1 also include:

[0052] S31: Reset the initial value of the element value in the station element table. It can be reset every morning, or it can be reset at other times.

[0053]A website element configuration table is set up in the background, and each element can be set to horizontal and vertical categories. When the user logs in to the front desk every day, a temporary site element table is automatically assigned to it, which is recorded in the form of an array. The initial value of each element is 0. Cached on the server, each user has one and only one element array every day, the value of the element is updated for each step of the operation performed by the user, the data of all users of the day is uniformly saved in the early morning of each day, and the cache is cleared. Server distribution, data needs to be aggregated first and then calculated. Set a fixed time to organize and c...

Embodiment 4

[0060] Example 4, see Figure 5 , one A device for predicting user off-grid, for implementing the above method, comprising:

[0061] The element table allocation unit 10, the user operation recording unit 20, the average active value calculation unit 30, the downward trend judgment unit 40, and the element value reset unit.

[0062] The element table allocation unit 10 is used for allocating the matrix type site element table to the registered users who log in, and setting the initial value of each element;

[0063] The matrix site element table of this embodiment includes horizontal columns and vertical columns, the horizontal column is user behavior classification, the user behavior classification includes: browsing, posting, commenting, sharing, deletion, the vertical column is at least one site function collection classification, site function classification Collection categories include: news, albums, logs, friends, BLOG.

[0064] The specific implementation method is...

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PUM

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Abstract

The invention discloses a method for forecasting whether a user is off network, which comprises the following steps: distributing matrix-type site elements to a registered user who logs in; setting the initial value of each element; recording all the operations of the registered user; summarizing the operations of the registered user; calculating an average active value of the user; judging whether the average active values of different users in the preset time present descending trend or not, if so, determining the user to be an off-network user; otherwise, returning to the step of distributing matrix-type site elements to the registered user who logs in, and setting the initial value of each element. The invention also discloses a device for forecasting whether the user is off network. The invention provides a user behavior excavation manner, which can be used for calculating the standard active value by matching with a certain algorithm, thereby forecasting the possibility of the user off network in advance from the trend of the active degree of the user, so that operators can take corresponding remedial measures.

Description

technical field [0001] The present invention relates to the field of Internet technology, and more particularly, to a method and device for predicting user off-network. Background technique [0002] With the continuous development of social informatization and the Internet, website operators often need to understand the behavior of users in the process of interacting with the website. [0003] The current social networking website off-network analysis generally uses the user's login time to judge. For example, if a user has not logged in for more than three months, it can be judged that the user has left the network. However, this method has a drawback. First of all, although it can basically be judged that the user has left the network, we cannot predict other behaviors of the user. For example, the user may have defected to other websites; The user is no longer interested in the original browsing content; or the user leaves because he does not like a certain function of t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 梁捷周耀庭
Owner ALIBABA (CHINA) CO LTD
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