There are several approaches for clustering real valued time series data. However, there is a paucity of approaches for discrete valued time series. This project will help address this shortage.
Impact
This work will present researchers with effective options for clustering discrete valued time series data.
Student Experience
One graduate student (formerly M.Sc., now Ph.D.) is involved in the project.
Countries
Greece
Impact
Research
Institutional Partner(s)
Athens University of Economics and Business
Community Partner(s)
Industry Partner(s)
Key Outcomes
Publications
Sponsorship
Federal
Sponsorship Details
NSERC Discovery grant. Canada Research Chairs program.
