O2O coupon usage big data prediction method

A prediction method and coupon technology, applied in data processing applications, commerce, instruments, etc., can solve problems such as unsatisfactory effects of real data sets, unsatisfactory prediction accuracy, unsatisfactory integrated learning effects, etc.

Inactive Publication Date: 2017-10-27
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

Most of the existing methods fail to perform multi-classifier ensemble learning or their ensemble learning effect is not ideal, and some methods do not deal with the feature construction selection and unbalanced data accordingly, resulting in unsatisfactory prediction accuracy. The prediction effect of the set is not ideal, the work done by the present invention has greatly improved the accuracy of big data in coupon usage prediction, and improved the practicability of the algorithm

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  • O2O coupon usage big data prediction method
  • O2O coupon usage big data prediction method
  • O2O coupon usage big data prediction method

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Embodiment 1

[0050] In order to further explain the solution of the present invention, the consumption records of coupons received by users from April 1, 2016 to June 15, 2016 are used as the training set, and the coupons collected by users from May 15, 2016 to July 31, 2016 are used as the training set. The behavior is a prediction set as an example to elaborate on this technical solution, refer to figure 1 , figure 1 A flow chart of an O2O coupon using big data prediction method provided in this embodiment:

[0051] Step 1: The collected user offline consumption and coupon collection behavior includes user ID, merchant ID, and coupon ID (null means no coupon consumption); discount rate: x\in[0,1] represents the discount rate; x: y means full x minus y, and the unit is yuan; the distance between the user's frequent activities and the nearest store of the merchant is x*500 meters (if it is a chain store, take the nearest store), x\in[0,10]; Null means no such information, 0 means less th...

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Abstract

The invention protects an O2O coupon usage big data prediction method. The method comprises the steps that 101, a historical consumption dataset of a user is subjected to preprocessing operation; 102, the historical consumption dataset of the user is marked, and a training set and a prediction set are divided and constructed; 103, the historical consumption dataset of the user is subjected to feature engineering construction; 104, feature selection and processing of unbalanced data are performed; 105, the data is subjected to multi-classifier integrated learning; and 106, coupon usage of the user is predicted through an established model according to historical consumption data of the user, and serving of an O2O coupon is optimized. According to the method, a prediction model is established mainly by processing the user consumption data and performing multi-classifier integrated learning on the data, therefore, the coupon usage of the user in the future is predicted, and serving of the O2O coupon is optimized.

Description

technical field [0001] The invention belongs to the field of intelligent information processing, and in particular relates to a big data prediction method for O2O coupon usage. 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 O2O (Online to Offline) consumption is the most eye-catching. The O2O industry is naturally associated with hundreds of millions of consumers, and various APPs record more than 10 billion user behavior records every day, making it one of the best combination points for big data research and commercial operations. Using coupons to rejuvenate old customers or attract new customers to shop is an important marketing method for O2O. However, randomly placed coupons cause meaningless disturbance to most users. For merchants, spamming coupons may reduce brand reputation, and it is difficult to estimate marketing costs. With the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
CPCG06Q30/0202G06Q30/0211
Inventor 王进范磊杨阳欧阳卫华邵帅李航邓欣胡峰李智星陈乔松
Owner CHONGQING UNIV OF POSTS & TELECOMM
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