Paper Info
Title
Analyzing the role of dimension arrangement for data visualization in radviz
Abstract
The Radial Coordinate Visualization (Radviz) technique has been widely used to effectively evaluate the existence of patterns in highly dimensional data sets A crucial aspect of this technique lies in the arrangement of the dimensions, which determines the quality of the posterior visualization Dimension arrangement (DA) has been shown to be an NP-problem and different heuristics have been proposed to solve it using optimization techniques However, very little work has focused on understanding the relation between the arrangement of the dimensions and the quality of the visualization In this paper we first present two variations of the DA problem: (1) a Radviz independent approach and (2) a Radviz dependent approach We then describe the use of the Davies-Bouldin index to automatically evaluate the quality of a visualization i.e., its visual usefulness Our empirical evaluation is extensive and uses both real and synthetic data sets in order to evaluate our proposed methods and to fully understand the impact that parameters such as number of samples, dimensions, or cluster separability have in the relation between the optimization algorithm and the visualization tool.
Year
DOI
Venue
2010
10.1007/978-3-642-13672-6_13
PAKDD (2)
Keywords
Field
DocType
optimization technique,optimization algorithm,radviz dependent approach,data visualization,synthetic data set,visualization tool,posterior visualization dimension arrangement,da problem,dimensional data,radviz independent approach,dimension arrangement,synthetic data,indexation
Data mining,Data set,Data visualization,Circle graph,Visualization,Computer science,Heuristics,Autonomous system (Internet),Optimization algorithm,Artificial intelligence,Synthetic data sets,Machine learning
Conference
Volume
ISSN
ISBN
6119
0302-9743
3-642-13671-0
Citations 
PageRank 
References 
20
0.92
11
Authors
3
Name
Order
Citations
PageRank
Luigi Di Caro119535.21
Vanessa Frias-Martinez221317.79
Enrique Frias-Martinez323817.11