User portrait generation method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of big data, and provides a user portrait generation method and device, computer equipment and a storage medium. The user portrait generation method comprises the following steps: obtaining an APP data list of a target user, generating a feature vector matrix taking the feature parameters as vector factors according to the characteristic parameters of each APP in the APP data list, obtaining a central vector matrix of each preset APP vector matrix set, determining a relationship parameter between the feature vector matrix and each center vector matrix, according to respective relationship parameters, determining a target vector matrix from each central vector matrix, taking an APP vector matrix set where the target vector matrix is located as atarget set, obtaining label information corresponding to the target set, and according to the label information, generating a user portrait of the target user, thereby determining a corresponding APPvector matrix set for a large amount of APP data of the target user through clustering simplification, obtaining simplified label information, more accurately describing features of the target user, and improving the analysis efficiency of the user portrait.

Description

technical field [0001] The present application relates to the technical field of big data, and in particular to a user portrait generation method, device, computer equipment and storage medium. Background technique [0002] With the development of information technology, user portrait analysis technology has emerged. User portrait is a tool and method to objectively and accurately describe target users. In the context of the era of big data, user information is flooded in the network, and each specific information of the user is abstracted into labels, and these labels are used to concretize the image of the user, so as to provide users with targeted services. [0003] In the process of actual operation, the user's attributes, behaviors and expectations are often connected with the most simple and life-like words. As a virtual representative of actual users, the user roles formed by user portraits are not constructed out of products and markets. The formed user roles are re...

AI Technical Summary

Problems solved by technology

[0004] In the prior art, most methods for generating user portraits use keyword extraction methods to generate user tags, but using keyword extraction methods to analyze user portraits has a certain limit on the amount of analyzed data. When analyzing data When the amount of data is huge, a large number of feature labels will be generated correspondingly. This analysis method will lead to weak analysis results and low analysis efficiency.

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