Talks and Poster Presentations (with Proceedings-Entry):
J. Bernard, C. Bors, M. Bögl, C. Eichner, T. Gschwandtner, S. Miksch, H. Schumann, J. Kohlhammer:
"Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series";
Talk: 9th International EuroVis Workshop on Visual Analytics (EuroVA),
2018-06-12; in: "EuroVis Workshop on Visual Analytics (EuroVA) 2018",
Eurographics Digital Library,
For the automatic segmentation of multivariate time series domain experts at first need to consider a huge space of alternative configurations of algorithms and parameters. We assume that only a small subset of these configurations needs to be computed and analyzed to lead users to meaningful configurations. To expedite this search, we propose the conceptualization of a segmentation workflow. First, with an algorithmic segmentation pipeline, domain experts can calculate segmentation results with different parameter configurations. Second, in an interactive visual analysis step, domain experts can explore segmentation results to further adapt and improve segmentation pipeline in an informed way. In the interactive analysis approach influences of algorithms, parameters, and different types of uncertainty information are conveyed, which is decisive to trigger selective and purposeful re-calculations. The workflow is built upon reflections on collaborations with domain experts working in activity recognition, which also defines our usage scenario demonstrating the applicability of the workflow.
Time series analysis, Visual Analytics
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Electronic version of the publication:
Project Head Silvia Miksch:
Visuelle Segmentierung und Labeling multivariater Zeitserien
Created from the Publication Database of the Vienna University of Technology.