Commodity pushing method and device, electronic equipment and computer readable storage medium

Abstract

The invention provides a commodity pushing method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of data statistics. The method comprises the following steps: acquiring user behavior information of a plurality of users, and determining user description information of each user based on associated commodities in the user behavior information; and then calculating the similarity among the plurality of users based on a similarity algorithm, determining a target user group taking the first user as the center, and pushing commodities involved by the first user to clients of the users in the target user group. According to the embodiment of the invention, the user description information is acquired, the similarity between the users is determined based on the user description information, then the target user group taking the first user as the central user is determined, and the commodity associated with the first user is pushed to the client of the user in the target user group, so that the method does not depend on the real information of the user, and the user experience is improved. The method can determine a clear target user, and has a better popularization effect for users in small and medium-sized industries.

Description

technical field [0001] The present application relates to the technical field of data statistics, and in particular, to a method, apparatus, electronic device, and computer-readable storage medium for pushing commodities. Background technique [0002] With the development of Internet business, in order to gain more users, obtain better user loyalty or provide users with personalized content, recommendation algorithms have been applied to various fields, including books, music, videos, news, movies, maps, etc. . [0003] In the existing recommendation algorithms, a large number of user groups and a large amount of user identity information are required, and they are all recommendation algorithms for big data users. Enterprises need a more personalized recommendation algorithm, and what they need is the accurate placement of advertisements. The existing recommendation algorithms cannot meet the above requirements. SUMMARY OF THE INVENTION [0004] The purpose of this appli...

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Problems solved by technology

[0004] The purpose of this application is to at least solve one of the above-mentioned technical defects, especially in the existing recommendation algorithms, which require a large number of user groups and a large amount of user identity information, all of which are recommendation algorithms for big data users, and for Enterprises with small customers cannot obtain a large amount of user information, and for small enterprises, what is needed is a more personalized recommendation algorithm and precise advertising. The existing recommendation algorithm cannot meet the above requirements defect

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