Details

Autor(en) / Beteiligte

• Rohlig, Martin
• Luboschik, Martin
• Schumann, Heidrun
• Bogl, Markus
• Alsallakh, Bilal
• Miksch, Silvia

Titel

Analyzing parameter influence on time-series segmentation and labeling

Ist Teil von

• 2014 IEEE Conference on Visual Analytics Science and Technology (VAST), 2014, p.269-270

Ort / Verlag

IEEE

Erscheinungsjahr

2014

Quelle

IEL

Beschreibungen/Notizen

• Reconstructing processes from measurements of multiple sensors over time is an important task in many application domains. For the reconstruction, these multivariate time-series can be automatically processed. However, the outcomes of automated algorithms often vary in quality and show strong parameter dependencies, making manual inspections and adjustments of the results necessary. We propose a visual analysis approach to support the user in understanding parameters' influences on these results. With our approach the user can identify and select parameter settings that meet certain quality criteria. The proposed visual and interactive design helps to identify relationships and temporal patterns, supports subsequent decision making, and promotes higher accuracy as well as confidence in the results.