System resource allocation method and device, and equipment

A system resource and allocation method technology, applied in the field of system resource allocation, can solve the problems of no solution, inability to accurately characterize user risk characteristics, and reduce user experience, and achieve the effect of strengthening generalization ability.

Pending Publication Date: 2021-05-25
INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are usually fewer samples of known user risks, and the sample data of known user risks may not be able to accurately characterize the risk characteristics of users under the new service type, thus affecting the accuracy of user risk prediction and affecting the allocation to corresponding users. The accuracy of user resources may lead to unreasonable resource allocation and reduce the user experience
[0004] For the above problems, no effective solution has been proposed

Method used

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  • System resource allocation method and device, and equipment
  • System resource allocation method and device, and equipment
  • System resource allocation method and device, and equipment

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Embodiment Construction

[0029]In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification Obviously, the described embodiments are only some of the embodiments in the description, not all of them. Based on one or more embodiments in the description, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the embodiments of the description.

[0030] In a scenario example provided by the embodiment of this specification, the system resource allocation method may be applied to a device performing system resource allocation, and the device may include a server, or may include a server cluster composed of multiple servers. For the target user, the server can extract ch...

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Abstract

The embodiment of the invention relates to the technical field of artificial intelligence, and discloses a system resource allocation method and device, and equipment, and the method comprises the steps: obtaining a specified information set with feature data used for representing user risk features, and a tag set; the specified information set at least comprises a prediction sample set and three reference sample sets; the label set comprises risk categories corresponding to the reference samples; correspondingly constructing at least three sub-classifiers by utilizing at least three reference sample sets and the label set; performing risk classification on the prediction sample by using each sub-classifier to obtain a risk classification result of the prediction sample relative to each sub-classifier and a misclassification cost of the prediction sample; and optimizing each sub-classifier according to the prediction sample set, the risk classification result of the prediction sample and the misclassification cost of the prediction sample to obtain each optimized sub-classifier, and allocating system resources to the target user based on the risk prediction result of each optimized sub-classifier for the target user.

Description

technical field [0001] This specification relates to the technical field of artificial intelligence, and in particular, relates to a system resource allocation method, device and equipment. Background technique [0002] With the rapid development of big data service platform technology, financial resource service types and alternative service channels are becoming more and more diverse and convenient, and user risk prediction is becoming more and more important for financial institutions. For example, for some online loan businesses with relatively convenient service channels, due to relatively little manual intervention, if user risk prediction is not accurate enough, there may be problems such as unreasonable resource allocation and poor user experience. [0003] At present, the commonly used user risk prediction methods are mainly classification methods based on supervised learning models. Through modeling based on known customer risk data, the trained model is used to pr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/08G06Q40/02G06Q40/04
CPCG06Q40/04G06N3/08G06Q40/03G06F18/2411G06F18/24155G06F18/214
Inventor 陈李龙王娜罗杰文张宏韬
Owner INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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