Resource spreading method and apparatus, server and computer readable storage medium

Abstract

The invention discloses a resource spreading method. The resource spreading method comprises the steps of obtaining a first resource spread by a first account number in a first user group; obtaining an influence of the first account number in the first user group, so as to determine a spreading amount of the first resource according to the influence; obtaining a first resource spreading tree of the first resource, wherein the first resource spreading tree is used for recording and buffering a spreading action of the first resource; according to the first resource spreading tree, user account numbers that do not receive the first resource in the first user group and the spreading amount, determining a target user account number spreading the first resource, and recording the target user account number to the first resource spreading tree; and spreading the first resource to the target user account number. The invention further discloses a resource spreading apparatus, a server and a storage medium. Based on a node spreading control grouped type treelike spreading manner, the probability that a user receives a repeated resource is reduced, and the quality of a resource with a largespreading amount is improved.

Description

technical field [0001] The present invention relates to the field of information dissemination, in particular to a resource dissemination method, device, server and computer-readable storage medium. Background technique [0002] At present, most of the popular online information dissemination platforms at home and abroad are based on following relationship, and the resources released by the resource publisher will be sent to the followers of the resource publisher. However, the information dissemination platform based on the following relationship has the following disadvantages: 1. Hot resources are often repeated among different publishers, and followers who overlap between different publishers tend to receive multiple highly similar resources, which seriously affects the resource reception of followers experience, which is not conducive to the maintenance of the follower relationship; 2. Resource publishers falsify the number of followers for profit, and the existence of ...

AI Technical Summary

Problems solved by technology

However, the information dissemination platform based on the following relationship has the following disadvantages: 1. Hot resources are often repeated among different publishers, and followers who overlap between different publishers tend to receive multiple highly similar resources, which seriously affects the resource reception of followers experience, which is not conducive to the maintenance of the follower relationship; 2. Resource publishers falsify the number of followers for profit, and the existence of a large number of zombie fans seriously affects other users' judgment of the resource quality of publishers; 3. The information acquisition advantage is weak Publishers often need strong innovation ability to maintain the quality of newly released resources in order to maintain the following relationship. When the test frequency of innovation ability increases or the time span increases, most followers will cancel the following relationship due to the decline in the quality of the publisher’s resources , when most of the publishers have a downward trend in the number of followers, it will seriously affect the user experience of the information dissemination platform based on the following relationship

The resource dissemination method based on the user's historical reading preference for algorithm recommendation currently has the following shortcomings: 1. The collected data, such as click-through rate, reading time, and reading completeness, may not represent the real intention of the user

In order to use the algorithm recommendation mechanism to increase the recommendation rate, many resource publishers write titles that do not match the content or publish exaggerated and bizarre content, which seriously affects the user experience

2. Similar resources will be repeatedly recommended. Plagiarism between publishers on different platforms, imitation between publishers within the platform, and identification errors in historical reading preferences will cause users on the platform to repeatedly receive similar resources.

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