TicketHub

Researchers at Purdue University have developed an all-in-one management application for IT and support tickets that leverages natural language processing to understand ticket context. By clustering based on context, trend analysis can be used to help enterprises improve efficiency and throughput. Clusters formed from ticket trends can be used to inform what ticket content may require more specialized training or enable users to find past solutions to similar problems that arise. This technology has applications in the IT & support software space, where it could be used as a standalone system or integrated into traditional systems.

Technology Validation: This technology has been validated through deployment at the Purdue University Rosen Center for Advanced Computing, where it has been found to improve the ticketing process and identify trends in ticket content.

Advantages:

-Context clustering of support tickets

-Trend analysis

-Improved efficiency makes a better experience for users

Applications:

-IT support systems

-AI/Machine Learning with Natural Language Processing (NLP)

-Data Analytics

TRL: 6

Intellectual Property:

Keywords: IT support software, natural language processing, NLP, support ticket clustering, trend analysis, IT support systems, AI/Machine Learning, data analytics, customer support automation, ticket management application, Artificial Intelligence, Data Science, data-driven, Machine Learning