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Fraud marking method and device based on multi-view learning

A multi-view, tagging technology, applied in the field of information processing, which can solve the problems of high acquisition cost, limited fraudulent tags, and prediction model limitations.

Pending Publication Date: 2019-10-22
SHANGHAI QIFU INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the field of anti-fraud, a real problem is that fraud tags are often limited due to the high cost of acquisition
In the case of insufficient samples, conventional forecasting models are greatly limited

Method used

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  • Fraud marking method and device based on multi-view learning
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  • Fraud marking method and device based on multi-view learning

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Embodiment Construction

[0070] The above description is only an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention, it can be implemented according to the contents of the description, and in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable , the specific embodiments of the present invention are enumerated below.

[0071] However, the example embodiments described below can be embodied in various forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and incorporate the concepts of the example embodiments Fully conveyed to those skilled in the art. The same reference numerals denote the same or similar parts in the drawings, and thus their repeated descriptions will be omitted.

[0072] Furthermore, the described features, ...

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PUM

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Abstract

The invention discloses a fraud marking method and device based on multi-view learning, and the method comprises the steps: obtaining a user data set; dividing the user data set into a marked data setand an unmarked data set; respectively training a plurality of view classifiers on the marked data set based on different views; judging and marking partial data in the unmarked data set by using theplurality of trained view classifiers; adding the marked data into a marked data set to form a new marked data set; circularly carrying out the action of the new marked data set until a preset stop condition is reached; fusing the plurality of view classifiers to generate a secondary classifier; and judging and marking the data by using the secondary classifier. According to the method, the interaction, advantage complementation and collaborative learning among views are exerted by utilizing different learning difficulties of the data in different views, so that the effect of performing fraudmarking by adopting less and lower-cost sample data is achieved.

Description

technical field [0001] The invention relates to the field of information processing, in particular to a method and device for fraud marking based on multi-view learning. Background technique [0002] With the vigorous development of Internet consumer finance, more and more people use online platforms to apply for business. The quick operation and simple process make mobile phones as the main application tool become the link between users and platforms, and between users and users. important medium. Fraud risk is one of the main risks faced by the Internet finance industry and an important part of credit risk management. [0003] In the field of anti-fraud, a real problem is that fraud tags are often limited due to the high cost of acquisition. In the case of insufficient samples, conventional forecasting models are greatly limited. What is needed is a method that reduces dependence on sample size, yet accurately flags fraud risks. [0004] The above information disclosed...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q40/00G06K9/62
CPCG06Q10/0635G06Q40/00G06F18/214
Inventor 孙涛陈雪清熊俊
Owner SHANGHAI QIFU INFORMATION TECH CO LTD
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