A method and a device for identifying abnormal users based on a random forest model

A user identification and random forest model technology, applied in the field of computer readable storage medium and abnormal user identification, can solve the problems of low accuracy and large amount of sample data, and achieve the effects of high accuracy, accelerated training process and fast processing speed.

Pending Publication Date: 2019-01-18
CHINA PING AN LIFE INSURANCE CO LTD
View PDF5 Cites 35 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present disclosure is to provide a method and device for identifying abnormal users based on a random forest model, electronic equipment, and a computer-readable storage medium, so as to overcome, at least to a certain extent, existing methods for identifying abnormal users that require a large amount of sample data and have low accuracy. low problem

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method and a device for identifying abnormal users based on a random forest model
  • A method and a device for identifying abnormal users based on a random forest model
  • A method and a device for identifying abnormal users based on a random forest model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concept of example embodiments to those skilled in the art. The described attributes, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0029] Exemplary embodiments of the present disclosure firstly provide a method for identifying abnormal users based on a random forest model, referring to figure 1 As shown, the method may include the following steps:

[0030] Step S11 , count sample data from historical user information according to preset attributes, and obtain classification labels of historical users, wherein the preset attributes include at least the first type of attri...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a method and a device for identifying abnormal users based on a random forest model, belonging to the technical field of big data. The method comprises the following steps: thesample data is counted from the information of a history user according to a preset attribute, wherein, the preset attribute comprises a first class attribute and a second class attribute, and the classification tag of the history user is obtained; a random forest model is trained using the sample data and the classification label, wherein in the training process, the first class of attributes corresponds to a first sampling probability, the second class of attributes corresponds to a second sampling probability, and the first sampling probability is greater than the second sampling probability; According to the preset attribute, the target data is counted from the information of the user to be identified, and the target data is processed through the trained random forest model to determine whether the user to be identified is an abnormal user. The present disclosure may reduce the amount of sample data required for the abnormal user identification method and improve the accuracy of identification.

Description

technical field [0001] The present disclosure relates to the technical field of big data, and in particular to a method and device for identifying abnormal users based on a random forest model, electronic equipment, and a computer-readable storage medium. Background technique [0002] The Internet and various Internet-based applications (Application, App for short) have greatly facilitated people's lives, but there are also some users who abuse the Internet or App services to obtain improper benefits, such as false users and false "fans" that appear on the Internet. ", malicious swiping orders, malicious advertisements and other abnormal users and abnormal behaviors have affected the normal operation of the website or App, and damaged the interests of operators and normal users. Therefore, it is necessary to identify and deal with these abnormal users. [0003] Most of the existing abnormal user identification methods are to establish a database of abnormal behavior, and the...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F16/2458G06K9/62
CPCG06F18/24323
Inventor 陈伟源
Owner CHINA PING AN LIFE INSURANCE CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products