Towards a user-defined visual-interactive definition of similarity functions for mixed data

2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 - Proceedings

Volumn , Issue , 2015, Pages 227-228

  Bernard, Jurgen ^a   Hutter, Marco ^a   Sessler, David ^a   Schreck, Tobias ^b   Behrisch, Michael ^b   Kohlhamme, Jorn ^a,c  

^a FRAUNHOFER IGD   (Germany)

^b UNIVERSITY OF KONSTANZ   (Germany)

^c DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

H.5.2 Information Systems : Information Interfaces and Presentation User Interfaces; I.5.3 Computing Methodologies : Pattern Recognition Clustering

Indexed keywords

CLUSTERING ALGORITHMS; GRAPHICAL USER INTERFACES;

CATEGORICAL DATA; COMPUTING METHODOLOGIES; DOMAIN EXPERTS; FEEDBACK MODEL; H.5.2 [INFORMATION SYSTEMS]: INFORMATION INTERFACES AND PRESENTATION - USER INTERFACES; MULTIVARIATE DATA; NUMERICAL DATA; SIMILARITY FUNCTIONS;

PATTERN RECOGNITION SYSTEMS;

EID: 84929467383     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/VAST.2014.7042503     Document Type: Conference Paper

References (3)

1. J. Bernard, D. Sessler, T. Ruppert, J. Davey, A. Kuijper, and J. Kohlhammer. User-based visual-interactive similarity definition for mixed data objects-concept and first implementation. In Int. Conf. in Central Europe on Comp. Graph., Vis. and Comp. Vis. (WSCG), 2014.
2. J. Liu, E. T. Brown, R. Chang, and C. E. Brodley. Dis-function: Learning distance functions interactively. In VAST, pages 83-92. IEEE, 2012.
3. G. M. H. Mamani, F. M. Fatore, L. G. Nonato, and F. V. Paulovich. User-driven feature space transformation. In Proceedings of EuroVis, pages 291-299. Eurographics Association, 2013.