18547328. TICKET TROUBLESHOOTING SUPPORT SYSTEM simplified abstract (MICROSOFT TECHNOLOGY LICENSING, LLC)
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 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Ticket Support Automation Technology
- 1.13 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 18547328 titled 'TICKET TROUBLESHOOTING SUPPORT SYSTEM
Simplified Explanation
The patent application describes a system that uses machine learning to provide ticket support by clustering support tickets based on the similarity of resolution commands.
Key Features and Innovation
- Utilizes machine learning model trained on clusters of support tickets
- Extracts commands used to resolve tickets and creates clusters based on similarity
- Identifies problem statements from resolved tickets and trains the model with them
- Predicts cluster number for new tickets and provides relevant resolution commands
Potential Applications
This technology can be applied in various industries that require ticket support systems, such as customer service, IT support, and help desks.
Problems Solved
- Efficiently categorizes and resolves support tickets
- Automates the process of providing relevant resolution commands
- Improves response time and customer satisfaction
Benefits
- Streamlines ticket support processes
- Increases efficiency and accuracy in ticket resolution
- Enhances user experience by providing timely and relevant support
Commercial Applications
Ticket Support Automation Technology for Customer Service and IT Help Desks This technology can revolutionize customer service and IT support operations by automating ticket categorization and resolution processes, leading to improved efficiency and customer satisfaction.
Prior Art
Readers can explore prior art related to machine learning models for ticket support systems, clustering algorithms for ticket categorization, and natural language processing for problem statement extraction.
Frequently Updated Research
Stay updated on the latest advancements in machine learning models for ticket support systems, clustering algorithms for ticket categorization, and natural language processing for problem statement extraction.
Questions about Ticket Support Automation Technology
How does this technology improve the efficiency of ticket support systems?
This technology improves efficiency by automating the categorization and resolution of support tickets based on clusters of similar commands.
What industries can benefit from implementing this ticket support automation technology?
Various industries such as customer service, IT support, and help desks can benefit from implementing this technology to streamline their ticket support processes.
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.
