Oracle international corporation (20240338594). PERFORMING AUTOMATED TICKET CLASSIFICATION simplified abstract
Contents
PERFORMING AUTOMATED TICKET CLASSIFICATION
Organization Name
oracle international corporation
Inventor(s)
Chunming Liu of Bellevue WA (US)
Kexin (Cathy) Cui of Bellevue WA (US)
Kai (Jason) Yin of Sammamish WA (US)
PERFORMING AUTOMATED TICKET CLASSIFICATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338594 titled 'PERFORMING AUTOMATED TICKET CLASSIFICATION
The abstract of the patent application describes a system where tickets generated in response to system incidents are automatically labeled using a trained machine learning model. These labels indicate whether the ticket needs user attention and/or the severity of the incident that prompted the ticket. Only tickets labeled as needing attention are provided to users for additional analysis, while tickets labeled as not needing user attention may be discarded or stored without being delivered to a user. Tickets may also be sorted according to the severity of the incident associated with the ticket to prioritize incidents with higher severity levels.
- Machine learning model automatically labels system incident tickets
- Labels indicate need for user attention and severity of incident
- Only tickets needing attention are provided to users for analysis
- Tickets not needing attention may be discarded or stored
- Tickets sorted by severity level to prioritize higher severity incidents
Potential Applications: - Incident management systems - Automated ticketing systems - IT support services
Problems Solved: - Efficiently prioritize system incidents - Reduce manual effort in ticket labeling - Improve incident response time
Benefits: - Faster resolution of critical system incidents - Enhanced efficiency in incident management - Improved user experience with IT support services
Commercial Applications: Title: Automated Incident Ticket Labeling System for IT Support Services This technology can be utilized by IT support companies to streamline incident management processes, improve response times, and enhance overall customer satisfaction. It can also be integrated into existing ticketing systems to automate the labeling and prioritization of system incidents.
Questions about Automated Incident Ticket Labeling System for IT Support Services:
1. How does the machine learning model determine the severity of system incidents? The severity of system incidents is determined based on various factors such as impact on system functionality, potential risks, and historical incident data.
2. What are the potential challenges in implementing an automated ticket labeling system for incident management? Some potential challenges include ensuring the accuracy of the machine learning model, integrating the system with existing ticketing platforms, and training users on the new system.
Original Abstract Submitted
according to certain implementations, tickets generated in response to system incidents may be automatically labeled utilizing a trained machine learning model, where such labels indicate () whether the ticket needs user attention and/or () a severity of the incident that prompted the ticket. only tickets labeled as needing attention may be provided to users (such as systems engineers) for additional analysis, and tickets labeled as not needing user attention may be discarded and/or stored without being delivered to a user for additional analysis. tickets may also be sorted according to a severity of the incident associated with the ticket, which may ensure that incidents with a higher severity level are prioritized over incidents with a lower severity level.
