Publikation: The Visual Exploration of Aggregate Similarity for Multi-Dimensional Clustering
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2015
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JOSÉ BRAZ, , ed. and others. IVAPP 2015 : Proceedings of the 6 th International Conference on Information Visualization Theory and Applications. SciTepress, 2015, pp. 40-50. ISBN 978-989-758-088-8
Zusammenfassung
We present a visualisation prototype for the support of a novel approach to clustering called TRIAGE. TRIAGE uses aggregation functions which are more adaptable and flexible than the weighted mean for similarity modelling. While TRIAGE has proven itself in practice, the use of complex similarity models makes the interpretation of TRIAGE clusterings challenging. We address this challenge by providing analysts with a linked, matrix-based visualisation of all relevant data attributes. We employ data sampling and matrix seriation to support both effective overviews and fluid, interactive exploration using the same visual metaphor for heterogeneous attributes. The usability of our prototype is demonstrated and assessed with the help of real-world usage scenarios from the cyber-security domain.
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IVAPP 2015 : Information Visualization Theory and Applications, 11. März 2015 - 14. März 2015, Berlin
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TWELLMEYER, James, Marco HUTTER, Michael BEHRISCH, Jörn KOHLHAMMER, Tobias SCHRECK, 2015. The Visual Exploration of Aggregate Similarity for Multi-Dimensional Clustering. IVAPP 2015 : Information Visualization Theory and Applications. Berlin, 11. März 2015 - 14. März 2015. In: JOSÉ BRAZ, , ed. and others. IVAPP 2015 : Proceedings of the 6 th International Conference on Information Visualization Theory and Applications. SciTepress, 2015, pp. 40-50. ISBN 978-989-758-088-8BibTex
@inproceedings{Twellmeyer2015Visua-31471,
year={2015},
title={The Visual Exploration of Aggregate Similarity for Multi-Dimensional Clustering},
isbn={978-989-758-088-8},
publisher={SciTepress},
booktitle={IVAPP 2015 : Proceedings of the 6 th International Conference on Information Visualization Theory and Applications},
pages={40--50},
editor={José Braz},
author={Twellmeyer, James and Hutter, Marco and Behrisch, Michael and Kohlhammer, Jörn and Schreck, Tobias}
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<dcterms:abstract xml:lang="eng">We present a visualisation prototype for the support of a novel approach to clustering called TRIAGE. TRIAGE uses aggregation functions which are more adaptable and flexible than the weighted mean for similarity modelling. While TRIAGE has proven itself in practice, the use of complex similarity models makes the interpretation of TRIAGE clusterings challenging. We address this challenge by providing analysts with a linked, matrix-based visualisation of all relevant data attributes. We employ data sampling and matrix seriation to support both effective overviews and fluid, interactive exploration using the same visual metaphor for heterogeneous attributes. The usability of our prototype is demonstrated and assessed with the help of real-world usage scenarios from the cyber-security domain.</dcterms:abstract>
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