Method and device for identifying data exception, server and medium

A technology for identifying data and anomalies, applied in the computer field, can solve problems such as large-scale manpower, poor judgment accuracy, and difficulty in ensuring large-scale data anomalies, and achieve the effects of reducing workload, meeting training requirements, and improving accuracy

Pending Publication Date: 2021-12-10
BEIJING WODONG TIANJUN INFORMATION TECH CO LTD +1
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, manual monitoring requires a lot of manpower, and it is difficult to ensure that personnel can detect abnormalities in large-scale data in a timely manner
However, since the data in the actual scene usually fluctuates, the accuracy of judging whether the data is abnormal is not good by setting the fluctuation threshold "one size fits all".

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
  • Method and device for identifying data exception, server and medium
  • Method and device for identifying data exception, server and medium
  • Method and device for identifying data exception, server and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] The present disclosure will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0021] It should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

[0022] figure 1 An exemplary architecture 100 to which the method for identifying data anomalies or the apparatus for identifying data anomalies of the present disclosure can be applied is shown.

[0023] Such as figure 1 As shown, the system architecture 100 may incl...

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 embodiment of the invention discloses a method and device for identifying data exception, a server and a medium. A specific embodiment of the method comprises: obtaining a target data sequence in a preset time period; determining a predicted value corresponding to the target data sequence; extracting a data feature index based on the target data sequence and the predicted value; and inputting the data feature indexes into a pre-trained autonomous learning model, and generating prompt information used for representing whether data exception exists or not. According to the embodiment, the workload of personnel is reduced, and the accuracy of data exception identification is improved.

Description

technical field [0001] The embodiments of the present disclosure relate to the field of computer technology, and in particular to a method, device, server and medium for identifying data anomalies. Background technique [0002] With the development of Internet technology, the scale of data is increasing day by day. For large-scale data, how to identify outliers in a timely and effective manner is of great significance for the normal operation of business systems and other aspects. [0003] In the prior art, it is often judged whether the data is abnormal by manually monitoring data changes or setting a fluctuation threshold. However, manual monitoring requires a lot of manpower, and it is difficult to ensure that personnel can detect abnormalities in large-scale data in a timely manner. However, since the data in the actual scene usually fluctuates, the accuracy of judging whether the data is abnormal by setting the fluctuation threshold "one size fits all" is not good. ...

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): G06K9/62G06F16/906
CPCG06F16/906G06F18/214
Inventor 司小婷肇斌杨勇王飞胡长建王蕾张伟沈力马俊
Owner BEIJING WODONG TIANJUN INFORMATION TECH 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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap