Datenanalyse und Visualisierung

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Wolfgang Jentner

Mitarbeiter

E-Mail: wolfgang.jentner(at)uni-konstanz.de
Telefon: +49 (0)7531 88-3941
Fax: -
Raum: C201
Adresse: Universität Konstanz
Fachbereich Informatik und Informationswissenschaft
Box D78
78457 Konstanz, Germany

Publikationen

Publications
2016
M. El-Assady, V. Gold, W. Jentner, M. Butt, K. Holzinger and D. A. Keim.
VisArgue - A Visual Text Analytics Framework for the Study of Deliberative Communication.
Proceedings of The International Conference on the Advances in Computational Analysis of Political Text (PolText2016), University of Zagreb, pages 31--36, 2016.
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W. Jentner, G. Ellis, F. Stoffel, D. Sacha and D. A. Keim.
A Visual Analytics Approach for Crime Signature Generation and Exploration.
The Event Event: Temporal & Sequential Event Analysis, IEEE VIS 2016 Workshop, to appear, 2016.
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W. Jentner, M. El-Assady, D. Sacha, D. Jäckle and F. Stoffel.
Dynamite: Dynamic Monitoring Interface for Task Ensembles.
IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2016 MC1) (Award - Notable Support for Streaming Analysis), 2016.
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2015
F. Wanner, W. Jentner, T. Schreck, A. Stoffel, L. Sharalieva and D. A. Keim.
Integrated visual analysis of patterns in time series and text data - Workflow and application to financial data analysis.
Information Visualization, DOI: 10.1177/1473871615576925, 2015.
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2014
M. El-Assady, W. Jentner, M. Stein, F. Fischer, T. Schreck and D. A. Keim.
Predictive Visual Analytics – Approaches for Movie Ratings and Discussion of Open Research Challenges.
Proceedings of the IEEE VIS 2014 Workshop Visualization for Predictive Analytics, 2014.
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F. Wanner, T. Schreck, W. Jentner, L. Sharalieva and D. A. Keim.
Relating interesting quantitative time series patterns with text events and text features (Best Paper Award).
IS&T/SPIE Electronic Imaging, pages 90170G--90170G, DOI: 10.1117/12.2039639, 2014.
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2013
M. El-Assady, D. Hafner, M. Hund, A. Jäger, W. Jentner, C. Rohrdantz, F. Fischer, S. Simon, T. Schreck and D. A. Keim.
Visual Analytics for the Prediction of Movie Rating and Box Office Performance.
VAST Challenge 2013 - Award for Effective Analytics, 2013.
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