Authors:
James Twellmeyer
1
;
Marco Hutter
1
;
Michael Behrisch
2
;
Jörn Kohlhammer
3
and
Tobias Schreck
2
Affiliations:
1
Fraunhofer IGD, Germany
;
2
University of Konstanz, Germany
;
3
Fraunhofer IGD and Technische Universität Darmstadt, Germany
Keyword(s):
Clustering, Information Visualisation, Visual Analytics, Similarity Functions, Aggregation Functions.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
Information and Scientific Visualization
;
Visual Data Analysis and Knowledge Discovery
;
Visualization Applications
Abstract:
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.