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Internet card user loss prediction method and system based on user portraits

A technology of user churn and prediction method, applied in neural learning methods, biological neural network models, instruments, etc., can solve problems such as poor accuracy, and achieve the effect of high prediction accuracy

Pending Publication Date: 2022-01-21
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The invention provides a method and system for predicting user churn of Internet cards based on user portraits, which are used to solve the technical problem of poor accuracy of existing user churn prediction methods

Method used

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  • Internet card user loss prediction method and system based on user portraits
  • Internet card user loss prediction method and system based on user portraits
  • Internet card user loss prediction method and system based on user portraits

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Experimental program
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Embodiment 1

[0070] Such as Figure 7 As shown, this implementation discloses a method for predicting the loss of Internet card users based on user portraits, including the following steps:

[0071] Analyzing the identity characteristics and behavior characteristics of Internet card users related to loss, and determining the key portrait data dimensions and key time-series behavior data dimensions of Internet card users; Degree of active entropy, the key time series behavior data dimension includes the number of days of abnormal behavior that characterizes the abnormal behavior of Internet card users;

[0072] Obtain key portrait data of different user dimensions and key time-series behavior data in different periods from historical data to construct a training data set, and mark the user loss category corresponding to the training data in the training data set; construct a deep learning model, and Using the marked training data in the training data set to train the deep learning model to...

Embodiment 2

[0077] Embodiment 2 Aiming at key issues such as current communication operators' existing user loss and maintenance, a method for predicting the loss of Internet card users based on user portraits is proposed. First, the user attributes, CDR (Call Detail Record), traffic Data and other data are cleaned, and the target user group required by the communication operator is extracted from the data set of each month, and each user is marked with a churn label according to the churn determination rule. Then, feature extraction is performed based on the data of each dimension of the user, which is mainly divided into four aspects, namely, the user's personal information, package and expenditure information, call detail records, and traffic usage behavior, especially for the latter two, according to the formula or algorithm extraction features to maximize the representation of the difference between normal users and churn users. The second step uses the user features and labels extra...

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Abstract

The invention discloses an internet card user churn prediction method and system based on a user portrait, and the method comprises the steps: determining a key portrait data dimension and a key time sequence behavior data dimension of an internet card user through analyzing the identity characteristics and behavior characteristics of the internet card user related to churn; the key portrait data dimension comprises the uncertainty and the activity entropy of the activity of the Internet card user behavior, and the key time sequence behavior data dimension comprises the number of abnormal behavior days of the abnormal behavior of the Internet card user; key portrait data of corresponding dimensions of different users and key time sequence behavior data of different periods are obtained from historical data to construct a training data set, the training data set is used to train the constructed deep learning model, and then the trained deep learning model is used to predict user loss. According to the method, when the feature dimension of the training data is selected, the active entropy of the user and the number of abnormal behavior days are newly added to reflect the loss behavior rule of different users, so that the prediction precision of the deep learning model obtained through training is higher.

Description

technical field [0001] The invention relates to the technical field of user churn prediction, in particular to a method and system for predicting Internet card user churn based on user portraits. Background technique [0002] With the rapid development of modern information technology and communication technology, users in the field of mobile communication can enjoy high-quality services at relatively low prices. The market competition is becoming increasingly fierce, the demand is gradually saturated, and the loss of original users is also becoming more and more serious. Among them, user churn refers to the user terminating the service contract with the enterprise or switching to services provided by other companies. According to Garter's survey data, the cost of developing a new user is 4 to 5 times the cost of maintaining an old user. Another study shows that if a company reduces the churn rate by 5%, it can increase profits by 25% to 85%. At present, my country's mobi...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06K9/62G06N3/04G06N3/08G06F111/08
CPCG06F30/27G06N3/04G06N3/08G06F2111/08G06F18/213G06F18/22G06F18/24G06F18/214
Inventor 吕丰钱凯吴帆任炬张尧学
Owner CENT SOUTH UNIV