User data processing method and device, computer equipment and storage medium

Abstract

The invention relates to a user data processing method and device, computer equipment and a storage medium. The method comprises the steps of obtaining multiple pieces of user data, wherein each pieceof user data comprises feature data of multiple dimensions; screening a plurality of target user data from the user data; according to the feature data of the target user data in each dimension and the weight corresponding to each dimension, determining the similarity degree between the target user data; clustering the target user data based on the similarity between the target user data to obtain the category to which each target user data belongs; training a classification model according to the target user data and the category to which the target user data belongs; classifying the residual user data after screening through the classification model obtained by training to obtain the category to which each piece of residual user data after screening belongs; and pushing information according to the category to which each piece of user data belongs. By adopting the method, the accuracy of user data classification can be improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a user data processing method, device, computer equipment and storage medium. Background technique [0002] With the development of computer technology, people rely more and more on the Internet to obtain all kinds of information. In order to provide users with products or services in a timely manner and avoid providing useless products or services as much as possible, it is usually determined according to the classification labels of user data. The target audience for the product or service. [0003] However, the classification of existing user data is mainly based on statistical user portraits. In this way, it is difficult to accurately judge the sparse behavior characteristics of users, and it is difficult to make judgments on the classification that user data really belongs to, resulting in the obtained The accuracy of classification results of user data is relat...

AI Technical Summary

Problems solved by technology

[0003] However, the classification of existing user data is mainly based on statistical user portraits. In this way, it is difficult to accurately judge the sparse behavior characteristics of users, and it is difficult to make judgments on the classification that user data really belongs to, resulting in the obtained The accuracy of classification results of user data is relatively low

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