Improving usage pattern quality by comparing different sequential pattern mining methods and the effect of considering additional user information

Frequent usage patterns generated can provide valuable information for several applications such as platform restructuring and recommendation. In this project, we aim to compare different practical methods, and to investigate the effect of user identity and user intention information on them. To that end, a technique and a framework need to be developed, in which frequent patterns are composed of more refined analysis result instead of simple frequent sequences of basic operations over all users’ behavior. The outcome of this project is expected to improve the user experience for the partner organization’s product and such methods can be also used in various relevant applications.

Faculty Supervisor:

Fred Popowich


Zelin Tian


Kinematicsoup Technologies Inc


Computer science


Media and communications


Simon Fraser University



Current openings

Find the perfect opportunity to put your academic skills and knowledge into practice!

Find Projects