Transaction mode portrait establishing method and device, medium and electronic device

Abstract

The invention relates to the field of user portraits, and discloses a transaction mode portrait establishing method and device, a medium and an electronic device. The method comprises the steps of obtaining a sample set comprising a plurality of intermediate accounts and feature value groups corresponding to the intermediate accounts; obtaining clustering features in a preset feature group according to the feature value group; obtaining a feature value corresponding to the clustering feature as a clustering feature value; clustering the intermediate accounts based on the clustering feature values, and dividing the intermediate accounts into a plurality of clusters; determining a transaction mode corresponding to the cluster according to the clustering feature value of the intermediate account in the cluster; when a request for establishing a transaction mode portrait of a target intermediate account is received, obtaining a feature value group of the target intermediate account; and determining a transaction mode of the target intermediate account based on the feature value corresponding to the clustering feature in the target intermediate account feature value group and the transaction mode corresponding to each cluster. According to the method, the accuracy of the transaction mode portrait is ensured, and the meticulous degree of depicting the transaction mode portrait is improved.

Description

technical field [0001] The present disclosure relates to the technical field of user portraits, in particular to a method, device, medium and electronic equipment for establishing a transaction mode portrait. Background technique [0002] With the popularization of mobile Internet applications such as mobile payment, it is becoming more and more important to use data to establish transaction model portraits for users. A good transaction model portrait can help Internet companies understand user preferences, achieve refined operations, and improve service levels. [0003] In the implementation of the prior art, only the data submitted by the user during registration are analyzed, such as age, gender, occupation and other data. Since these data may not be closely related to the actual business of Internet companies, these data are of little use in helping to improve the actual business. [0004] The disadvantage of the existing technology is that the user's trading habits are...

AI Technical Summary

Problems solved by technology

Since these data may not be closely related to the actual business of Internet companies, these data are of little use in helping to improve the actual business

[0004] The disadvantage of the existing technology is that the existing big data analysis method does not describe the user's trading habits carefully enough, the transaction model portrait established for the user is too rough, and the transaction model portrait has low accuracy in expressing user characteristics

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