Abstract
The traditional data analysis tools support strong computational capabilities and numerous standard visualization techniques. However, they provide little visual interactions due to the fact that the tools maintain a wide applicability to diverse data domains, and thus any inherent meanings associated with the data domains are hardly allowed. To cover these limitations, we propose to augment Mat lab, one of the widely used data analysis tools and computational languages, by imposing the capabilities of handling semantic objects so that diverse essential interaction capabilities could be allowed such as brushing-and-linking, details-on-demand, and dynamic interactive updating on visualization. In our demonstration, we will show our audience how to import semantic data, how visual interactions are occurred, and how these functionalities are convenient using the movie similarity graph data set.
Original language | English |
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Pages | 1093-1096 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2013 |
Event | 2013 13th IEEE International Conference on Data Mining Workshops, ICDMW 2013 - Dallas, TX, United States Duration: 2013 Dec 7 → 2013 Dec 10 |
Conference
Conference | 2013 13th IEEE International Conference on Data Mining Workshops, ICDMW 2013 |
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Country/Territory | United States |
City | Dallas, TX |
Period | 13/12/7 → 13/12/10 |
Keywords
- Clustering dimension reduction
- Interactive visualization
- Visual analytics
ASJC Scopus subject areas
- Software