18547328. TICKET TROUBLESHOOTING SUPPORT SYSTEM simplified abstract (Microsoft Technology Licensing, LLC)

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 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 resolution commands from prior tickets, creates clusters based on command similarity, extracts problem statements from resolved tickets in each cluster, and trains a machine learning model to identify cluster numbers for each cluster. When a new support ticket is received, the system extracts a problem statement, predicts a cluster number using the trained model, and provides resolution commands from the corresponding cluster to the user.

• The system extracts resolution commands from support tickets
• Clusters tickets based on similarity of resolution commands
• Trains a machine learning model with problem statements from resolved tickets
• Predicts a cluster number for new tickets
• Provides resolution commands based on predicted cluster number

Potential Applications

This technology can be applied in customer support systems, IT helpdesks, and any other ticket-based support services that require efficient resolution of issues.

Problems Solved

This technology helps in automating the ticket resolution process, improving response times, and ensuring consistent and accurate support for users.

Benefits

The benefits of this technology include faster ticket resolution, improved customer satisfaction, reduced workload for support agents, and increased efficiency in support operations.

Potential Commercial Applications

One potential commercial application of this technology is in software companies that provide customer support services, where it can streamline the ticket resolution process and enhance the overall customer experience.

Possible Prior Art

Prior art in this field may include existing ticketing systems that use machine learning for ticket classification and routing, as well as systems that analyze ticket data for support trends and patterns.

How does the system handle new types of issues that do not fit into existing clusters?

The system may need to be periodically retrained with new data to adapt to emerging support issues and create new clusters as needed.

What measures are in place to ensure the privacy and security of the ticket data being used for training the machine learning model?

The system should have robust data protection mechanisms in place to safeguard sensitive information contained in support tickets and ensure compliance with data privacy regulations.

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.