Method and system for automatically dividing user levels

A technology of automatic classification and user level, applied in special data processing applications, text database clustering/classification, instruments, etc., can solve the problems of inconsistent classification standards, long manual operation time, large data volume, etc., to achieve user experience effects. Good, save labor cost, improve the effect of accuracy

Active Publication Date: 2016-12-07
武汉斗鱼鱼乐网络科技有限公司
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Problems solved by technology

However, in actual operation, the method of manually classifying user levels is often carried out with a large degree of subjectivity, making the classification standards inconsistent; in addition, in the scenario of massive data, user data often has many dimensions and data The volume is large, and relying on manual judgment to classify users is often inaccurate, the coverage rate is not high enough, and repetitive work is likely to lead to mistakes, and the manual operation time is long, the classification efficiency is low, and the labor cost is relatively high

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  • Method and system for automatically dividing user levels
  • Method and system for automatically dividing user levels

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Embodiment Construction

[0037] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0038]Cluster analysis is one of the key issues in the field of data mining and machine learning. It is widely used in data mining, pattern recognition, decision support, machine learning and image segmentation. It is one of the most important data analysis methods. The K-means algorithm is the most widely used partition-based hard clustering analysis algorithm, and it is a representative of a typical prototype-based objective function clustering method. It is a certain distance from the data point to the prototype as the optimized objective function. , using the method of finding the extremum of the function to obtain the adjustment rule of the iterative operation. The K-means algorithm uses the Euclidean distance as the similarity measure, which seeks the optimal classification corresponding to an initial cluster center vector V, so...

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Abstract

This invention discloses a method and system for automatically dividing user levels, and relates to the technical field of data mining. The method comprises the steps of: S1, selecting original sample data; S2, selecting at least one type of user characteristic as a dimension for calculating distance; S3, determining number K of classifications; S4, selecting K users from the original sample data as initial classification centers; S5, measuring distance from the rest of each user in the original sample data to each of the current classification center; classifying the rest of each user into a nearest classification to finish the division of K classifications; S6, recalculating the classification center of each classification; S7, iterating the S5 and the S6; and stopping the iterative operation till a new classification center is equal to the original classification center or till the variable quantity is less than a specified threshold, so that the currently divided K classifications are the user level classifications required to be divided. The method can automatically divide the user levels, is precise and efficient, and can save the labor cost.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a method and system for automatically classifying user levels. Background technique [0002] With the rapid development of Internet technology, more and more users can use terminals such as computers and mobile phones to perform entertainment and work on various websites through the Internet. And for all kinds of websites, its user base also becomes larger and larger with the continuous increase of the number of users. In order to meet the increasing user base, improve the service quality of the website, and enhance the user experience, it is usually necessary to classify users. For example, in various business scenarios of a live video website, in order to stimulate users' viewing interest, improve viewing volume and user experience, a series of user levels in the website are usually divided. [0003] At present, when major websites classify user levels, they generally ado...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/00G06F16/35G06F16/951
Inventor 龚灿
Owner 武汉斗鱼鱼乐网络科技有限公司
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