Title :
Towards a user-defined visual-interactive definition of similarity functions for mixed data
Author :
Bernard, Jurgen ; Hutter, Marco ; Sessler, David ; Schreck, Tobias ; Behrisch, Michael ; Kohlhamme, Jorn
Author_Institution :
Fraunhofer IGD, Rostock, Germany
Abstract :
The 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.
Keywords :
data visualisation; interactive systems; 2D data landscape; categorical data; domain experts; mental similarity notion; mixed data; multivariate data objects; numerical feedback models; similarity functions; user-defined visual-interactive definition; visual-interactive user feedback; Correlation; Data models; Educational institutions; Electronic mail; Numerical models; Optimization; Uncertainty; H.5.2 [Information Systems]: Information Interfaces and Presentation — User Interfaces; I.5.3 [Computing Methodologies]: Pattern Recognition — Clustering;
Conference_Titel :
Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on
Conference_Location :
Paris
DOI :
10.1109/VAST.2014.7042503