Schreck, Tobias ; Sharalieva, Lyubka ; Wanner, Franz ; Bernard, Jürgen ; Ruppert, Tobias ; Landesberger von Antburg, Tatiana ; Bustos, Benjamin (2012):
Visual Exploration of Local Interest Points in Sets of Time Series.
pp. 239-240, IEEE Press, New York, IEEE Conference on Visual Analytics Science and Technology 2012. Proceedings, DOI: 10.1109/VAST.2012.6400534,
[Conference or Workshop Item]
Abstract
Visual analysis of time series data is an important, yet challenging task with many application examples in fields such as financial or news stream data analysis. Many visual time series analysis approaches consider a global perspective on the time series. Fewer approaches consider visual analysis of local patterns in time series, and often rely on interactive specification of the local area of interest. We present initial results of an approach that is based on automatic detection of local interest points. We follow an overview-first approach to find useful parameters for the interest point detection, and details-on-demand to relate the found patterns. We present initial results and detail possible extensions of the approach.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2012 |
| Creators: | Schreck, Tobias ; Sharalieva, Lyubka ; Wanner, Franz ; Bernard, Jürgen ; Ruppert, Tobias ; Landesberger von Antburg, Tatiana ; Bustos, Benjamin |
| Title: | Visual Exploration of Local Interest Points in Sets of Time Series |
| Language: | English |
| Abstract: | Visual analysis of time series data is an important, yet challenging task with many application examples in fields such as financial or news stream data analysis. Many visual time series analysis approaches consider a global perspective on the time series. Fewer approaches consider visual analysis of local patterns in time series, and often rely on interactive specification of the local area of interest. We present initial results of an approach that is based on automatic detection of local interest points. We follow an overview-first approach to find useful parameters for the interest point detection, and details-on-demand to relate the found patterns. We present initial results and detail possible extensions of the approach. |
| Publisher: | IEEE Press, New York |
| Uncontrolled Keywords: | Business Field: Visual decision support, Research Area: Semantics in the modeling process, Research Area: Generalized digital documents, Forschungsgruppe Visual Search and Analysis (VISA), Data analysis, Time series data visualization |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Event Title: | IEEE Conference on Visual Analytics Science and Technology 2012. Proceedings |
| Date Deposited: | 12 Nov 2018 11:16 |
| DOI: | 10.1109/VAST.2012.6400534 |
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