Multi-dimensional data exception detection method and device, readable storage medium and electronic device

Abstract

The invention relates to a multi-dimensional data exception detection method and device, a readable storage medium and an electronic device. The method comprises: acquiring target data input by a userin a form, and the target data are multi-dimensional data; determining K first sample data similar to the target data in a first sample data set, wherein the target data and the first sample data inthe first sample data set have the same dimension space; and determining whether the target data is abnormal or not according to the abnormal condition of each first sample data in the K first sampledata. Thus, the form designer can automatically detect whether the target data is abnormal or not, manual detection is not needed, the manual participation degree is reduced, and intelligence of multi-dimensional data abnormal condition detection is improved. Besides, different first sample data can be utilized to adapt to different service scenes, and the defects that in the prior art, when different service scene requirements are met through a hard coding mode, the applicability is poor, and the system processing performance is reduced are avoided.

Description

technical field [0001] The present disclosure relates to the technical field of data processing, and in particular, to a multi-dimensional data anomaly detection method, device, readable storage medium, and electronic equipment. Background technique [0002] A form is a commonly used data collection tool on a web page. In the business approval process, the data entered by users can be collected through the form. The form designer is used to design the form. The existing form designer cannot automatically match or detect the business data in the form it designs, especially for complex and changeable multi-dimensional business data, it is difficult to intelligently diagnose, and it is necessary to rely on manual detection of abnormal data entered by users in the form situation, making the form designer less intelligent. Or, it can only be detected by hard-coding according to specific business scenarios, resulting in poor functional applicability. In different business scenar...

AI Technical Summary

Problems solved by technology

The existing form designer cannot automatically match or detect the business data in the form it designs, especially for complex and changeable multi-dimensional business data, it is difficult to intelligently diagnose, and it is necessary to rely on manual detection of abnormal data entered by users in the form situation, making the form designer less intelligent

Or, it can only be detected by hard coding according to specific business scenarios, resulting in poor functional applicability. In different business scenarios, it is necessary to rewrite specific codes, which is time-consuming and laborious, and reduces system processing performance.

Images