A method and system for automatically classifying users

Abstract

The present invention relates to the technical field of data mining; a user level automatic segmentation method and system. Said method comprises: selecting original sample data; selecting at least one user feature to act as a dimension for calculating distance; determining a number K of classifications; randomly picking K number of users from the original sample data to act as initial class centers; measuring the distance of each remaining user in the original sample data to each current class center, and sorting each remaining user to the nearest class, thereby completing segmentation of K number of classes; recalculating the class centers of each class; repeating the iteration of S5 and S6 until the new class centers are equivalent to the original class centers or stopping iterative operations when the degree of variation is less than a specified threshold, and the currently segmented K number of classifications are considered the user level classifications which need to be segmented. The method may achieve user level automatic segmentation which is accurate, efficient, and which saves on labor costs.

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...

AI Technical Summary

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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