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User identification model training method, electronic equipment and computer storage medium

A technology of user identification and model training, applied in the field of e-books, can solve problems such as low user retention rate, achieve accurate recommendation and improve user retention rate

Pending Publication Date: 2021-11-02
ZHANGYUE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the inventor found in the implementation process that there are at least the following defects in the prior art: the user retention rate is still low

Method used

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  • User identification model training method, electronic equipment and computer storage medium
  • User identification model training method, electronic equipment and computer storage medium
  • User identification model training method, electronic equipment and computer storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0038] figure 1 A schematic flowchart of a method for training a user identification model provided according to Embodiment 1 of the present invention is shown. Wherein, the user identification model training method provided in this embodiment is executed on the client side or the server side, for example, it can be implemented by a mobile phone terminal, a computer terminal, a reader, and / or an e-book application client in a smart wearable device, or The e-book application server executes.

[0039] Such as figure 1 As shown, the method includes:

[0040] Step S110: Determine the user attribute of the first user according to the historical behavior records of the first user of the e-book application, wherein the user attribute is a retained user or a lost user, and the retained user is a user who meets specific requirements when using the e-book application, and the lost user is A user is a user who does not meet certain requirements when using the e-book application.

[0...

Embodiment 2

[0054] figure 2 A schematic flowchart of a method for training a user identification model provided according to Embodiment 2 of the present invention is shown. Wherein, the user identification model training method provided in this embodiment is a further optimization of the method in the first embodiment.

[0055] Such as figure 2 As shown, the method includes:

[0056] Step S210: Determine the user attribute of the first user according to the historical behavior records of the first user of the e-book application, wherein the user attribute is a retained user or a lost user, and the retained user is a user who meets specific requirements when using the e-book application. A user is a user who does not meet certain requirements when using the e-book application.

[0057] Step S220, extracting user behavior features consistent with user attributes from historical behavior records, and constructing a set of behavior feature words representing user behavior features.

[0...

Embodiment 3

[0068] image 3 A schematic flowchart of a method for training a user identification model provided according to Embodiment 3 of the present invention is shown. Wherein, the user identification model training method provided in this embodiment is a further optimization of the method in the first embodiment.

[0069] Such as image 3 As shown, the method includes:

[0070] Step S310, determine the user attribute of the first user according to the historical behavior records of the first user of the e-book application, wherein the user attribute is a retained user or a lost user, and the retained user is a user who meets specific requirements when using the e-book application, and the lost user is A user is a user who does not meet certain requirements when using the e-book application.

[0071] Step S320, counting the proportion of lost customers and / or retained customers, and forming a transition probability matrix.

[0072] Specifically, according to the specific definiti...

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PUM

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Abstract

The invention discloses a user identification model training method, electronic equipment and a computer storage medium. The method comprises the following steps: determining user attributes according to historical behavior records of users, wherein the user attributes are retained users or lost users; extracting user behavior features conforming to the user attributes from the historical behavior records, constructing a behavior feature word set, and training a user identification model, wherein the user identification model is used for predicting the user attributes and outputting the user attributes and corresponding behavior feature words. According to the scheme, the user identification model is obtained through training according to the behavior feature word set representing the user behavior features, the user identification model can predict the user attributes and output the user attributes and the corresponding behavior feature words, and the output user attributes and the corresponding behavior feature words can serve as reference bases of e-book recommendation. Therefore, accurate recommendation is realized, and the user retention rate is improved.

Description

technical field [0001] The invention relates to the technical field of electronic books, in particular to a user identification model training method, electronic equipment and a computer storage medium. Background technique [0002] With the continuous development of technology and society, e-books have gradually replaced traditional paper books. Various electronic products, such as smartphones, tablet computers, and e-readers, all support the installation of e-reading applications and have e-book reading functions. [0003] At present, various e-reading applications emerge in endlessly, how to retain users is the ultimate goal of each e-reading application. In the prior art, products that the user may like are usually recommended to the user based on historical reading content or based on the user's interest, so as to increase the retention rate of the user. [0004] However, the inventor found during implementation that at least the following defects exist in the prior ar...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06K9/62G06Q30/06
CPCG06F16/9535G06Q30/0631G06F18/211
Inventor 孟帅屈晓航
Owner ZHANGYUE TECH CO LTD