E-commerce discount coupon use probability prediction method based on integrated model

An integrated model and probability prediction technology, applied in business, data processing applications, character and pattern recognition, etc., can solve problems such as inability to meet e-commerce coupon usage probability, large generalization error, and easy overfitting of a single classification model. , to achieve the effect of improving prediction accuracy, reducing operating costs, and reducing generalization errors

Inactive Publication Date: 2018-11-23
GUANGDONG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Most of the existing coupon forecasting technologies are based on the user’s purchase behavior data to make predictions based on a single classification model. However, when the amount of data is large, a single classification model is prone to overfitting, and the generalization error is large, which affects the final value of the coupon. The prediction of the probability of using coupons cannot meet the prediction needs of e-commerce for the probability of using coupons

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  • E-commerce discount coupon use probability prediction method based on integrated model
  • E-commerce discount coupon use probability prediction method based on integrated model
  • E-commerce discount coupon use probability prediction method based on integrated model

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Embodiment 1

[0031] Such as figure 1 Shown is the flow chart of the method for predicting the use probability of electric business coupons based on the integrated model of the present invention, including the following steps:

[0032] S1. Count the online and offline historical consumption data of the user and perform preprocessing, the preprocessing includes eliminating data whose missing rate exceeds a set threshold and filling missing data to obtain a first data set;

[0033] S2. Perform feature extraction on the data in the first data set in step S1 to obtain the features to be analyzed, and construct a feature system, which includes merchant features, coupon features, user features, user and merchant combination features, and other features; Features, coupon features, user features, user-merchant combination features, and other features are listed in Table 1, Table 2, Table 3, Table 4, and Table 5 respectively;

[0034] Table 1 Merchant features include a list of features

[0035] ...

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Abstract

The invention relates to the technical field of data mining, and particularly relates to an e-commerce discount coupon use probability prediction method based on an integrated model. According to thee-commerce discount coupon use probability prediction method based on the integrated model, the integrated model comprising a primary learner and a secondary learner is constructed, and in combinationwith the advantages of a specific single model in the prediction of discount coupon use probability, the defects of single model prediction are avoided. In the case of large sample data, the prediction accuracy is improved, and the generalization error of the prediction model is reduced. The e-commerce can build the integrated model through the technology to more accurately predict the probability value of a user to use the discount coupon and to decide whether to issue the discount coupon to the user according to the probability value, thereby reducing the operation cost of the merchant andbetter achieving a promotion effect desired by the merchant.

Description

technical field [0001] The present invention relates to the technical field of data mining, and more specifically, relates to a method for predicting the usage probability of e-commerce coupons based on an integrated model. Background technique [0002] With the improvement and popularization of mobile devices, mobile Internet + all walks of life have entered a stage of rapid development, among which e-commerce consumption is the most eye-catching. According to incomplete statistics, there are at least 10 start-up companies in the e-commerce industry with a valuation of hundreds of millions, and there are also tens of billions of giants. The e-commerce industry is connected to hundreds of millions of consumers, and various APPs record more than 10 billion user behavior and location records every day, thus becoming one of the best combination points for big data scientific research and commercial operation. Using coupons to revitalize old users or attract new customers to sh...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06K9/62
CPCG06Q30/0202G06F18/2411G06F18/214
Inventor 石纯一石涛李卫军
Owner GUANGDONG UNIV OF TECH
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