Microsoft technology licensing, llc (20240135323). TICKET TROUBLESHOOTING SUPPORT SYSTEM simplified abstract
Contents
- 1 TICKET TROUBLESHOOTING SUPPORT SYSTEM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TICKET TROUBLESHOOTING SUPPORT SYSTEM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
TICKET TROUBLESHOOTING SUPPORT SYSTEM
Organization Name
microsoft technology licensing, llc
Inventor(s)
Udayan Kumar of Kirkland WA (US)
Rakesh Jayadev Namineni of Sammamish WA (US)
TICKET TROUBLESHOOTING SUPPORT SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240135323 titled 'TICKET TROUBLESHOOTING SUPPORT SYSTEM
Simplified Explanation
The patent application describes systems and methods for providing ticket support using a machine learning model trained with clusters of support tickets based on the similarity of resolution commands. The system extracts commands used to resolve prior tickets, creates clusters of resolved tickets based on the similarity of commands, and trains a machine learning model with the extracted problem statements to identify a cluster number for each cluster. When a new support ticket is received, the system extracts a problem statement from the new ticket, predicts a cluster number using the trained machine learning model, and provides commands used to resolve prior tickets in the corresponding cluster to the user.
- The system uses machine learning to predict the cluster of a new support ticket based on its problem statement.
- Commands used to resolve similar issues in the predicted cluster are provided to assist in resolving the new ticket.
Potential Applications
This technology can be applied in customer support systems, IT helpdesks, and any other ticket-based support services.
Problems Solved
1. Efficiently providing support by leveraging past ticket resolutions. 2. Improving the accuracy and speed of ticket resolution.
Benefits
1. Faster resolution times for support tickets. 2. Consistent and accurate support provided to users.
Potential Commercial Applications
Optimizing customer support operations with automated ticket resolution systems.
Possible Prior Art
Prior art may include existing ticket support systems that use machine learning for ticket categorization and resolution.
Unanswered Questions
How does the system handle new types of issues that do not match any existing clusters?
The system may need to be updated with new data and retrained to handle novel issues effectively.
What measures are in place to ensure the privacy and security of the data extracted from support tickets?
Data security protocols and encryption methods may be implemented to protect sensitive information contained in support tickets.
Original Abstract Submitted
systems and methods for providing ticket support using a machine learning model trained using clusters of support tickets that are clustered based on similarity of resolution commands are provided. the system extracts commands used to resolve prior tickets and creates clusters of resolved tickets based on similarity of the commands. for each cluster, problem statements are extracted from the resolved tickets. the system trains a machine learning model with the extracted problem statements to identify a cluster number for each cluster. with a new support ticket, the system extracts a problem statement from the new ticket and identifies a predicted cluster number by applying the trained machine learning mode! to the problem statement from the new ticket. based on the predicted cluster number, one or more commands used to resolve the prior tickets in the cluster corresponding to the predicted cluster number are accessed and provided to a requesting user.
