Visualization for knowledge discovery
โ Scribed by Georges Grinstein; John C. Sieg Jr.; Stuart Smith; Marian G. Williams
- Publisher
- John Wiley and Sons
- Year
- 1992
- Tongue
- English
- Weight
- 715 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
โฆ Synopsis
Although the fields of data visualization and automated knowledge discovery (AKD) share many goals, workers in each field have been reluctant to adopt the tools and methods of the other field. Many AKD researchers discourage the use of visualization tools because they believe that dependence on human steering will impede the development of numerical or analytical descriptions of complex data. Many visualization researchers are concerned that their present platforms are being pushed to the limits of their performance by the most advanced visualization techniques and are therefore unwilling to incur the perceived overhead of having a database system mediate access to the data. We argue that these attitudes are somewhat short-sighted and that the techniques of these two communities are complementary. We discuss a specific visualization system that we have developed and describe the obstacles that must be overcome in integrating it into an AKD system.
๐ SIMILAR VOLUMES
This paper uses the techniques of knowledge discovery in databases (KDD) and data visualization as a methodology to uncover significant clusters in the ownership of risky financial assets. Partitioning by medoids and data visualization identifies two significant clusters among risky asset holders. C