Time Series Motif/Discord Discovery Under Context
| Title | Time Series Motif/Discord Discovery Under Context |
|---|---|
| Summary | How we can find the repeated or odd patterns in a large time series that is under influence of multiple contexts? |
| Keywords | |
| TimeFrame | |
| References | https://www.cs.ucr.edu/~eamonn/Matrix_Profile_Tutorial_Part1.pdf
https://www.cs.ucr.edu/~eamonn/Matrix_Profile_Tutorial_Part2.pdf |
| Prerequisites | Data Mining Course |
| Author | |
| Supervisor | Hadi Fanaee |
| Level | Master |
| Status | Open |
This is a fantastic opportunity to work with Alfa Laval, a world's leader and pioneer in heat transfer, centrifugal separation and fluid handling. During the project, you will have this opportunity to gain access to real-life industrial IoT data and gain first-hand experience with such kind of valuable data.
The goal of this project is to extend Matrix Profile Algorithm (state-of-the-art time series motif/discord discovery and one of revolutionary solutions in the recent decade) for time series under influence of multiple contexts. The dataset comes from Alfa Laval industrial machines.
Read more about Matrix Profile: https://www.cs.ucr.edu/~eamonn/Matrix_Profile_Tutorial_Part1.pdf https://www.cs.ucr.edu/~eamonn/Matrix_Profile_Tutorial_Part2.pdf
Detailed discussion is possible at my office (E505) with a previous appointment (hadi.fanaee@hh.se)
