User identification method and device, apparatus and storage medium

Abstract

The invention relates to the field of data analysis, specifically uses a user classification model to identify a target user, and discloses a user identification method and device, an apparatus and astorage medium. The method comprises: obtaining offline image data and online data of a to-be-identified user; performing image processing on the offline image data to obtain offline data of the to-be-identified user; taking the offline data and the online data as user data of the to-be-identified user, and performing data preprocessing on the user data to obtain feature data of the to-be-identified user; inputting the feature data of the to-be-identified user into a pre-trained user classification model to obtain a classification probability of the to-be-identified user; and if the classification probability of the to-be-identified user is greater than a user classification threshold, determining the to-be-identified user as a target user. The accuracy of offline data entry and the recognition accuracy of the target user based on the user characteristics are improved.

Description

technical field [0001] The present application relates to the field of data analysis, and in particular to a user identification method, device, equipment and storage medium. Background technique [0002] At present, when identifying a target user for a user, most of the existing methods are based on business rules to analyze user characteristics, so as to identify the target user based on the analyzed user characteristics. However, this method will be affected by personal subjectivity, and it is prone to data omissions, and cannot fully analyze all features, resulting in incomplete identification of user data features. Moreover, the establishment of business rules is based on manual observation and data comparison, so user data features cannot be completely and accurately distinguished, so when identifying target users according to such rules, the identification accuracy rate is low. [0003] Therefore, how to perform identification based on user characteristics to improve...

AI Technical Summary

Problems solved by technology

However, this method will be affected by personal subjectivity, and it is prone to data omissions, and cannot fully analyze all features, resulting in incomplete identification of user data features.

Moreover, the establishment of business rules is based on manual observation and data comparison, so the characteristics of user data cannot be completely and accurately distinguished, so when identifying target users according to such rules, the recognition accuracy is low

Images