Information pushing method and device based on user behaviors, equipment and storage medium

Abstract

The invention relates to a big data analysis technology, and discloses a user behavior-based information pushing method, which comprises the steps of establishing data association between a user and collection equipment through a preset matching principle; constructing burying point data, collecting behavior data of a user, analyzing the behavior data, and storing the behavior data in a non-relational database NoSQL in the form of an event model table; analyzing and processing the behavior data to obtain target data; performing clustering analysis on the target data based on a K-means clustering algorithm to obtain M parts of clustering data, and obtaining a user group corresponding to each part of clustering data to obtain M user groups; and matching the service information of each user group according to a preset triggering mechanism, and pushing the service information to the user groups. The invention also relates to a blockchain technology, and the service information of the usergroup is stored in the blockchain. The service information is pushed to the user groups with the same preferences according to the user preferences, so that the service pushing efficiency is improved.

Description

technical field [0001] This application relates to the technical field of big data analysis, and in particular to an information push method, device, device and storage medium based on user behavior. Background technique [0002] Pushing information to users through user behavior data usually involves the cooperation and linkage between multiple departments, mainly involving the following links: activity design, customer group positioning, user reach, effect tracking, etc.; the above processes exist Long closed-loop period, high communication cost, shallow effect analysis and other issues. [0003] In order to solve the above problems, the existing technology judges the user's preference information by collecting user data and analyzing the user's interaction with a certain page or element, and pushes information to all or part of the users. However, this technology does not It can target user groups with the same preference information, resulting in low efficiency of pushi...

AI Technical Summary

Problems solved by technology

[0002] When pushing information to users through user behavior data, it usually involves cooperation and linkage between multiple departments, mainly involving the following links: activity design, customer group positioning, user reach, effect tracking, etc.; the above-mentioned processes exist Problems such as long closed-loop period, high communication cost, shallow effect analysis, etc.

[0003] In order to solve the above problems, the existing technology judges the user's preference information by collecting user data and analyzing the user's interaction with a certain page or element, and pushes information to all or part of the users. However, this technology does not Can target user groups with the same preference information, resulting in low efficiency of pushing information

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