Machine-learning based anomaly detection for heterogenous data sources
US10459827B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 22, 2016 |
| Grant date | Oct 29, 2019 |
| Priority date | — |
| Expiry date | Apr 9, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of an automated anomaly detection system are disclosed that can detect anomalous data from heterogeneous data sources. The anomaly detection system can provide an automated system that identifies data anomalies within data sets received from application host systems. The anomaly detection system may identify patterns using machine learning based on data set characteristics associated with the each data set. The anomaly detection system may generate a model that can be applied to existing data sets received from the application host systems in order to automatically identify anomalous data sets. The anomaly detection system may automatically identify the anomalous data sets and implement appropriate actions based on the determination.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.