US Patent Application 17661960. Predictive Severity Matrix simplified abstract
Contents
Predictive Severity Matrix
Organization Name
Inventor(s)
Matthew Louis Nowak of Midlothian VA (US)
Christopher Mcdaniel of Glen Allen VA (US)
Michael Anthony Young, Jr. of Henrico VA (US)
Predictive Severity Matrix - A simplified explanation of the abstract
This abstract first appeared for US patent application 17661960 titled 'Predictive Severity Matrix
Simplified Explanation
The patent application describes a method that uses machine learning models to determine the severity of potential incidents for an entity.
- Machine learning models are used to establish severity designations for potential incidents.
- Data from asset ownership, development operations tools, and severity matrix are compiled.
- The compiled data is used to determine a relationship with new metric data.
- Based on the determined relationship, a new entry is predicted for the severity matrix data.
- A notification is then generated to inform about the predicted severity designation.
Original Abstract Submitted
Aspects described herein may use machine learning models to establishing severity designations for associating with a potential occurrence of an incident of an entity. Asset ownership data, development operations tools metric data, and severity matrix data are compiled and a relationship between the compiled data and new metric data is determined. Based upon the determined relationship, a new entry to add to the severity matrix data is predicted and a notification of the same is thereafter outputted.
