Duesytech Online Extension

This project aims to enable Duesytech Online to provide services to match a customer’s technology service needs with the technologist or technician (tech) who is best equipped to provide that service. This matching is achieved through Machine Learning (ML) algorithms that are applied to find the best match given all the criteria set by the customer. The customer-tech match system will be integrated with an online store, where customers can buy deeply discounted consumer goods and technology supplies. There are several significant challenges in this area, such as discovering and maturing ML algorithms to match customers’ needs for technology services with techs, the sparse nature of the current data set, and testing ML algorithms against large sets of data. This project will implement technological advances in the area of ML technologies to overcome some of these difficulties.
The results of the proposed research will mature Duesytech to provide customers with more robust tech match service as well as enhanced the virtual mall shopping experience.

Faculty Supervisor:

Terry Peckham;George Ding

Student:

Partner:

Audio Concepts

Discipline:

Computer science

Sector:

Retail trade

University:

Saskatchewan Polytechnic

Program: