Faculty Advisor

Claypool, Mark L.

Center

Silicon Valley, California

Abstract

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.

Publisher

Worcester Polytechnic Institute

Date Accepted

March 2017

Major

Computer Science

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Advisor Department

Computer Science

Project Center

Silicon Valley, California

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