Name
Abstract | ||
|---|---|---|
Analysis tools such as Matlab, R, and SAS support a myriad of built-in computational functions and various standard visualization techniques. However, most of them provide little interaction from visualizations mainly due to the fact that the tools treat the data as just numerical vectors or matrices while ignoring any semantic meaning associated with them. To solve this limitation, we augment Matlab, one of the widely used data analysis tools, with the capability of directly handling the underlying semantic objects and their meanings. Such capabilities allow users to flexibly assign essential interaction capabilities, such as brushing-and-linking and details-on-demand interactions, to visualizations. To demonstrate the capabilities, two usage scenarios in document and graph analysis domains are presented. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2501511.2501521 | IDEA@KDD |
Keywords | Field | DocType |
semantic meaning,augmenting matlab,graph analysis domain,analysis tool,details-on-demand interaction,data analysis tool,numerical vector,essential interaction capability,interactive visual environment,usage scenario,built-in computational function,underlying semantic object,clustering,dimension reduction,visual analytics,interactive visualization | Analysis tools,Data mining,Dimensionality reduction,MATLAB,Computer science,Visual analytics,Power graph analysis,Interactive visualization,Artificial intelligence,Cluster analysis,Machine learning,Creative visualization | Conference |
Citations | PageRank | References |
1 | 0.48 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changhyun Lee | 1 | 2681 | 136.12 |
| Jaegul Choo | 2 | 556 | 46.81 |
| Duen Horng Chau | 3 | 1260 | 86.87 |
| Haesun Park | 4 | 3546 | 232.42 |