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Electronic commerce time sequence data anomaly detection method and system

An e-commerce, time-series technology, applied in digital data authentication, data processing applications, commerce, etc., can solve the problem of not being able to detect abnormal data in e-commerce data well

Inactive Publication Date: 2015-09-16
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0010] Based on this, it is necessary to provide an anomaly detection method and system for e-commerce time series data in view of the fact that the existing technology cannot detect abnormal data of e-commerce data well

Method used

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  • Electronic commerce time sequence data anomaly detection method and system
  • Electronic commerce time sequence data anomaly detection method and system
  • Electronic commerce time sequence data anomaly detection method and system

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Embodiment Construction

[0027] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0028] Such as figure 2 Shown is a work flow chart of an abnormality detection method for e-commerce time series data of the present invention, including:

[0029] Step S201 includes: acquiring time-series-based e-commerce data, executing step S202 for each data in the e-commerce data, and executing step S202 data as data to be detected;

[0030] Step S202, including: selecting the N-period e-commerce data adjacent to the data to be detected as the window statistical data, performing quantile statistics on the window statistical data, so as to determine the normal value upper boundary and the normal value lower boundary in the window statistical data Boundary, the data in the window statistical data outside the range of normal values ​​determined by the upper boundary of the normal value and the lower boundary of the normal value is...

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Abstract

The invention discloses an electronic commerce time sequence data anomaly detection method and a system. The method comprises steps: electronic commerce data based on a time sequence are acquired; an Nth phase electronic commerce data adjacent to to-be-detetced data are selected as window statistical data, quantile statistics is carried out on the window statistical data, a normal value upper boundary and a normal value lower boundary in the window statistical data are thus determined, and data out of a normal value range determined by the normal value upper boundary and the normal value lower boundary in the window statistical data are abnormal data; and the abnormal data serve as an application interface for being called by a demand side. Through benchmark detection, time sequence fluctuation identification based on a robust statistics method is realized, and the method and the system of the invention are applied to various distribution conditions. According to different electronic commerce service scenes and different data distribution forms, data anomaly can be automatically found out.

Description

technical field [0001] The invention relates to the technical field related to e-commerce, in particular to an abnormal detection method and system for e-commerce time series data. Background technique [0002] A time series is an ordered collection of individual observation records arranged in chronological order. In e-commerce business, time series usually contains a large amount of data over time. The analysis of time series can reveal the inherent laws of e-commerce business movement, change and development, especially for abnormal data, which often includes Therefore, how to quickly and effectively detect these abnormalities is a work of great significance. For example, sometimes the order data is abnormally large, which may mean huge market opportunities behind it; the abnormality of profit data Growth may mean that there are places to reduce product costs or increase profits that need to be located and tapped; while an abnormal decrease in the number of users may mea...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/00G06F21/31
Inventor 刘朋飞牟川李亮
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
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