Technometrics
A linear iteration time layout algorithm for visualising high-dimensional data
Proceedings of the 7th conference on Visualization '96
An informal information-seeking environment
Journal of the American Society for Information Science - Special issue on current research in human-computer interaction
Snap-together visualization: can users construct and operate coordinated visualizations?
International Journal of Human-Computer Studies - Empirical evaluation of information visualizations
ConMan: a visual programming language for interactive graphics
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
The Application Visualization System: A Computational Environment for Scientific Visualization
IEEE Computer Graphics and Applications
Refining Initial Points for K-Means Clustering
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
A Hybrid Layout Algorithm for Sub-Quadratic Multidimensional Scaling
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
Fast multidimensional scaling through sampling, springs and interpolation
Information Visualization
Improving hybrid MDS with pivot-based searching
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
Self organization of a massive document collection
IEEE Transactions on Neural Networks
Information Visualization - Special issue on coordinated and multiple views in exploratory visualization
A pivot-based routine for improved parent-finding in hybrid MDS
Information Visualization - Special issue of selected and extended InfoVis 03 papers
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In visualising multidimensional data, it is well known that different types of data require different types of algorithms to process them. Data sets might he distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This suggests that hybrid combinations of appropriate algorithms might also successfully address other characteristics of data. This paper presents a system and framework in which a user can easily explore hybrid algorithms and the data flowing through them. Visual programming and a novel algorithmic architecture let the user semiautomatically define data flows and the co-ordination of multiple views.