Visualization for knowledge discovery
| Autor: | Stuart Smith, Marian G. Williams, John C. Sieg, Georges Grinstein |
|---|---|
| Rok vydání: | 1992 |
| Předmět: |
Creative visualization
Operations research business.industry Computer science media_common.quotation_subject Data science Field (computer science) Theoretical Computer Science Visualization Human-Computer Interaction Data visualization Knowledge extraction Artificial Intelligence Overhead (computing) business Software media_common |
| Zdroj: | International Journal of Intelligent Systems. 7:637-648 |
| ISSN: | 1098-111X 0884-8173 |
| Popis: | 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. © 1992 John Wiley & Sons, Inc. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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