Talks and Poster Presentations (with Proceedings-Entry):
T. Lammarsch, W. Aigner, A. Bertone, S. Miksch, A. Rind:
"Mind the Time: Unleashing the Temporal Aspects in Pattern Discovery";
Talk: Fourth International EuroVis Workshop on Visual Analytics held in Europe (EuroVA 2013),
- 2013-06-18; in: "Proceedings of the Fourth International EuroVis Workshop on Visual Analytics held in Europe (EuroVA 2013)",
M. Pohl, H. Schumann (ed.);
Temporal Data Mining is a core concept of Knowledge Discovery in Databases handling time-oriented data. State-of-the-art methods are capable of preserving the temporal order of events as well as the information in between. The temporal nature of the events themselves, however, can likely be misinterpreted by current algorithms. We present a new definition of the temporal aspects of events and extend related work for pattern finding not only by making use of intervals between events but also by utilizing temporal relations like meets, starts, or during. The result is a new algorithm for Temporal Data Mining that preserves and mines additional time-oriented information.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Electronic version of the publication:
Project Head Silvia Miksch:
HypoVis: Modellierung von Hypothesen mit Visual Analytics Methoden zur Analyse der Vergangenheit und der Vorhersage der Zukunft
Created from the Publication Database of the Vienna University of Technology.