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Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data
(The Eurographics Association, 2018)
The segmenting and labeling of multivariate time series data is applied in different domains, e.g. activity recognition or sensor states. This involves several steps of (pre-) processing, segmenting, and labeling of time ...
Integrating Predictions in Time Series Model Selection
(The Eurographics Association, 2015)
Time series appear in many different domains. The main goal in time series analysis is to find a model for given time series. The selection of time series models is done iteratively based, usually, on information criteria ...
A Visual Analytics Approach to Segmenting and Labeling Multivariate Time Series Data
(The Eurographics Association, 2014)
Many natural and industrial processes such as oil well construction are composed of a sequence of recurring activities. Such processes can often be monitored via multiple sensors that record physical measurements over time. ...
Multi-Ensemble Visual Analytics via Fuzzy Sets
(The Eurographics Association, 2023)
Analysis of ensemble datasets, i.e., collections of complex elements such as geochemical maps, is widespread in science and industry. The elements' complexity arises from the data they capture, which are often multivariate ...
Quantifying Uncertainty in Multivariate Time Series Pre-Processing
(The Eurographics Association, 2019)
In multivariate time series analysis, pre-processing is integral for enabling analysis, but inevitably introduces uncertainty into the data. Enabling the assessment of the uncertainty and allowing uncertainty-aware analysis, ...
Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series
(The Eurographics Association, 2018)
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 ...