Self-service user group expansion method and device, computer device and storage medium

By using a self-service user group expansion method, and leveraging customer tag sorting and business information filtering features to train a classification model, the low efficiency of traditional user group expansion models is solved, achieving efficient user group expansion.

CN114925290BActive Publication Date: 2026-05-12XIAMEN AIRLINES CO LTD
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Patent Information

Application Number
CN202210628061.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-06-06
Publication Date
2026-05-12
Estimated Expiration
2042-06-06

AI Technical Summary

Technical Problem

Traditional user group expansion algorithm model building process is characterized by long modeling cycles, numerous business scenarios, and the need for customization of multiple models, resulting in low modeling efficiency.

Method used

This paper presents a self-service user group expansion method. By obtaining customer tags of the seed group, sorting them according to importance parameters and filtering features based on business information, training a classification model, expanding the user group, and obtaining a target group that matches the seed group.

Benefits of technology

It enables business personnel to independently select feature variables and train algorithm models, greatly improving the modeling efficiency of user group expansion and saving manpower, time and management costs.

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Abstract

The application relates to a self-service user group expansion method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: obtaining customer labels of a seed population; sorting the customer labels according to importance parameters to obtain sorted features; screening the sorted features according to input business information; training a classification model corresponding to the business information based on the screened sorted features to obtain an expansion model of the seed population; and expanding the user group in the full population through the expansion model to obtain a target group matched with the seed population. The method can sort the characteristic variables of the seed group according to the importance, and then the business personnel can select the characteristic variables and select different algorithm models according to the seed population and the importance of the characteristic variables of the seed population, so that efficient modeling is realized, and then the highly similar population to the seed population is automatically found from the population to be expanded for the business personnel to analyze and expand.
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