Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data

Kurzanzeige
dc.contributor.authorBernard, Jürgen
dc.contributor.authorSessler, David
dc.contributor.authorBehrisch, Michael
dc.contributor.authorHutter, Marco
dc.contributor.authorSchreck, Tobias
dc.contributor.authorKohlhammer, Jorn
dc.date.accessioned2015-02-24T14:32:33Z
dc.date.available2015-02-24T14:32:33Z
dc.date.issued2014eng
dc.description.abstractThe creation of similarity functions based on visual-interactive user feedback is a promising means to capture the mental similarity notion in the heads of domain experts. In particular, concepts exist where users arrange multivariate data objects on a 2D data landscape in order to learn new similarity functions. While systems that incorporate numerical data attributes have been presented in the past, the remaining overall goal may be to develop systems also for mixed data sets. In this work, we present a feedback model for categorical data which can be used alongside of numerical feedback models in future.eng
dc.description.versionpublished
dc.identifier.doi10.1109/VAST.2014.7042503eng
dc.identifier.urihttp://kops.uni-konstanz.de/handle/123456789/30005
dc.language.isoengeng
dc.subject.ddc004eng
dc.titleTowards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Dataeng
dc.typeINPROCEEDINGSeng
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kops.citation.bibtex
@inproceedings{Bernard2014Towar-30005,
  year={2014},
  doi={10.1109/VAST.2014.7042503},
  title={Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data},
  isbn={978-1-4799-6227-3},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={2014 IEEE Conference on Visual Analytics Science and Technology, Paris, France, 9-14 October 2014, Proceedings},
  pages={227--228},
  editor={Min Chen ...},
  author={Bernard, Jürgen and Sessler, David and Behrisch, Michael and Hutter, Marco and Schreck, Tobias and Kohlhammer, Jorn}
}
kops.citation.iso690BERNARD, Jürgen, David SESSLER, Michael BEHRISCH, Marco HUTTER, Tobias SCHRECK, Jorn KOHLHAMMER, 2014. Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data. IEEE Conference on Visual Analytics Science and Technology (VAST), 2014. Paris, 9. Okt. 2014 - 14. Okt. 2014. In: MIN CHEN ..., , ed.. 2014 IEEE Conference on Visual Analytics Science and Technology, Paris, France, 9-14 October 2014, Proceedings. Piscataway, NJ: IEEE, 2014, pp. 227-228. ISBN 978-1-4799-6227-3. Available under: doi: 10.1109/VAST.2014.7042503deu
kops.citation.iso690BERNARD, Jürgen, David SESSLER, Michael BEHRISCH, Marco HUTTER, Tobias SCHRECK, Jorn KOHLHAMMER, 2014. Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data. IEEE Conference on Visual Analytics Science and Technology (VAST), 2014. Paris, Oct 9, 2014 - Oct 14, 2014. In: MIN CHEN ..., , ed.. 2014 IEEE Conference on Visual Analytics Science and Technology, Paris, France, 9-14 October 2014, Proceedings. Piscataway, NJ: IEEE, 2014, pp. 227-228. ISBN 978-1-4799-6227-3. Available under: doi: 10.1109/VAST.2014.7042503eng
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kops.conferencefieldIEEE Conference on Visual Analytics Science and Technology (VAST), 2014, 9. Okt. 2014 - 14. Okt. 2014, Parisdeu
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source.title2014 IEEE Conference on Visual Analytics Science and Technology, Paris, France, 9-14 October 2014, Proceedingseng
temp.internal.duplicates<p>Keine Dubletten gefunden. Letzte Überprüfung: 07.01.2015 15:32:53</p>deu

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