View source for 18133607. AUTOMATED GENERATION OF TRAINING DATA FOR AN ARTIFICIAL-INTELLIGENCE BASED INCIDENT RESOLUTION SYSTEM simplified abstract (International Business Machines Corporation)

=AUTOMATED GENERATION OF TRAINING DATA FOR AN ARTIFICIAL-INTELLIGENCE BASED INCIDENT RESOLUTION SYSTEM=


==Organization Name==

[[:Category:International Business Machines Corporation|International Business Machines Corporation]]


[[Category:International Business Machines Corporation]]

==Inventor(s)==

[[:Category:Shirley M. Han of New York NY (US)|Shirley M. Han of New York NY (US)]][[Category:Shirley M. Han of New York NY (US)]]

[[:Category:Rama Kalyani T. Akkiraju of Cupertino CA (US)|Rama Kalyani T. Akkiraju of Cupertino CA (US)]][[Category:Rama Kalyani T. Akkiraju of Cupertino CA (US)]]

[[:Category:Xiaotong Liu of San Jose CA (US)|Xiaotong Liu of San Jose CA (US)]][[Category:Xiaotong Liu of San Jose CA (US)]]

[[:Category:Salil Ahuja of Washington DC (US)|Salil Ahuja of Washington DC (US)]][[Category:Salil Ahuja of Washington DC (US)]]

[[:Category:Isabell Sippli of Metzingen (DE)|Isabell Sippli of Metzingen (DE)]][[Category:Isabell Sippli of Metzingen (DE)]]

==AUTOMATED GENERATION OF TRAINING DATA FOR AN ARTIFICIAL-INTELLIGENCE BASED INCIDENT RESOLUTION SYSTEM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18133607 titled 'AUTOMATED GENERATION OF TRAINING DATA FOR AN ARTIFICIAL-INTELLIGENCE BASED INCIDENT RESOLUTION SYSTEM

**Simplified Explanation:**
The patent application describes a system that detects incident data and resolution data in monitored data from an IT environment. It then correlates this data based on changes in health metrics, stores it in a database, trains a machine learning model, and deploys it to provide resolution recommendations for new incident data.

**Key Features and Innovation:**
* Detection of incident and resolution data in monitored IT environment data
* Correlation of data based on changes in health metrics
* Storage of correlated data in a database as a training dataset
* Training of a machine learning model using the training dataset
* Deployment of the trained model to provide resolution recommendations for new incident data

**Potential Applications:**
This technology can be applied in various industries where incident resolution is critical, such as IT support services, network monitoring, and cybersecurity.

**Problems Solved:**
The technology addresses the challenge of efficiently correlating incident and resolution data in complex IT environments to provide timely and accurate resolution recommendations.

**Benefits:**
* Improved incident resolution efficiency
* Enhanced decision-making based on correlated data
* Automation of resolution recommendations for faster response times

**Commercial Applications:**
The technology can be utilized by IT service providers, cybersecurity firms, and companies with large IT infrastructures to streamline incident resolution processes and improve overall system health.

**Prior Art:**
Potential areas to search for prior art related to this technology include machine learning models for incident resolution, data correlation techniques in IT environments, and automated recommendation systems for IT support.

**Frequently Updated Research:**
Stay informed on advancements in machine learning models for incident resolution, data correlation algorithms, and IT automation technologies to enhance the capabilities of this system.

**Questions about IT Incident Resolution:**
1. How does the system detect changes in health metrics to correlate incident and resolution data?
2. What are the key factors considered in training the machine learning model for resolution recommendations?


==Original Abstract Submitted==

An embodiment includes detecting incident data and resolution data in monitored data collected while monitoring an information technology (IT) environment. The embodiment correlates the incident data with the resolution data according to a detected change in health metrics data from the monitored data. The embodiment stores the correlated incident data and resolution data as a training dataset stored in a database and then trains a machine learning model using the training dataset. The embodiment deploys the trained machine learning model such that the trained machine learning model provides resolution recommendation in response to receiving new incident data.



[[Category:G06N3/08]]
[[Category:G06Q30/04]]
[[Category:CPC_G06N3/08]]