Juniper Networks is a company selling networking hardware and software. When a customer needs assistance with a product, a customer support case is opened. The case can go through many stages before being resolved. The route a case takes to get to the resolver is currently human-controlled. This project aimed to assist case routing through the use of machine learning. We developed a system that can use a pipeline of data including previously resolved cases to model the relationship between a case and the engineer responsible for solving the problem. We used a deep learning neural network to create a system that could predict both the resolving group and engineer achieving up to 96% accuracy when predicting the 10 most likely groups, and 42% when predicting the 10 most likely engineers.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Ding, Ziyan
•  Perez, Joseph William
• Wang, Xuanzhe

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-031917-195025

Advisor

• Claypool, Mark L.

Year

• 2017

Center

• Silicon Valley, California Project Center - MQP

Sponsor

• Juniper Networks

Date created

• 2017-03-19

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright