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K-Means-algorithm-based direct broadcast platform user subdivision method and system

A live broadcast platform and user technology, applied in computing, computer parts, data processing applications, etc., can solve the problems of difficult marketing, reduced user favorability, user harassment, etc., and achieve the effect of improving accuracy and improving user satisfaction.

Inactive Publication Date: 2016-11-16
WUHAN DOUYU NETWORK TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But at present, for the subdivision of users, it is only divided manually according to certain established conditions, which is inefficient and cannot effectively and comprehensively divide the characteristics of users
Due to the relatively single feature dimension of manual division, the divided user groups are not accurate. When the salesperson matches the marketing plan according to the converted user groups, they cannot well control the user's preferences and habits, making marketing difficult. And the user has the feeling of being harassed, and the user's favorability is reduced, which increases the risk of user loss

Method used

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  • K-Means-algorithm-based direct broadcast platform user subdivision method and system
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  • K-Means-algorithm-based direct broadcast platform user subdivision method and system

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Embodiment Construction

[0036] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0037] see figure 1 As shown, the embodiment of the present invention provides a method for subdividing live platform users based on the K-Means algorithm, comprising the following steps:

[0038] A: Collect the user's basic information data and behavior information data from the server, and select the user's indicators within the sampling time as sample data. The sample data includes M indicators of N users; among them, the user's M indicators include the user's effective viewing time, The number of valid viewing days of the user, the number of barrage sent by the user, the number of virtual gifts given by the user, the viewing time of the user watching the game anchor, the number of barrage sent by the user when watching the game anchor, the number of virtual gifts given by the user to the game anchor, The viewing time of users watching ent...

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Abstract

The invention discloses a K-Means-algorithm-based direct broadcast platform user subdivision method and system, relating to the field of data mining. The method comprises the steps of (A) collecting the basic information data and behavior information data of users from a server, selecting the indexes of users in a sampling time as sample data, wherein the sampling data comprises M indexes of N users, (B) carrying out preprocessing and standardization processing on the sample data, and (C) using K-Means algorithm to carry out clustering, calculating the class to which each user belongs, and constructing a user subdivision group according to the class to which each user belongs in the sample data. The user subdivision group can be obtained according to the indexes of the users, and the division precision is high.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a K-Means algorithm-based user segmentation method and system for a live broadcast platform. Background technique [0002] Due to the rapid development of the live broadcast industry, the scale of platform users has increased, and the background and behavior characteristics of users are different. In order to understand the needs and behavior characteristics of users at different levels, provide personalized marketing strategies, and reasonably segment users, It can help companies better target target users and provide differentiated services. But at present, for user segmentation, it is only divided manually according to certain established conditions, which is inefficient and cannot effectively and comprehensively divide user characteristics. Due to the relatively single feature dimension of manual division, the divided user groups are not accurate. When the salesperson matches the ...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q50/00G06K9/62H04N21/258H04N21/442
CPCH04N21/25891H04N21/44204H04N21/44213H04N21/44218G06Q30/0201G06Q50/01G06F18/23213
Inventor 程晓歌吴瑞诚
Owner WUHAN DOUYU NETWORK TECH CO LTD
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