2008 International Conferences on Computational Intelligence for Modelling, Control and Automation; Intelligent Agents, Web Technologies and Internet Commerce; and Innovation in Software Engineering Information Visualization: Which Is the Most Appropriate Technique to Represent Data Mining Results? Vienna, Austria December 10-December 12 ISBN: 978-0-7695-3514-2
Data mining (DM) is a research area that has been contributing in the search for implicit knowledge that can give support to decision making. However, the analysis of the results obtained by using the techniques of DM is not an easy task. Such difficulty can be minimized, by using techniques of information visualization. But the issue is: which will be the most appropriate technique for each type of result to be analyzed? To help in the choice of techniques, this paper presents an evaluation of techniques for information visualization. Such task was accomplished by using the method known as Analysis of Characteristics, having as result the analysis on the effectiveness when using techniques of geometric and iconographical information visualization, mainly in relation to the results obtained with the application of K-means algorithm.
Index Terms:
Data mining, information visualization, evaluation of characteristics.
Citation:
Emerson Rabelo, Maria Dias, Clélia Franco, Roberto C. S. Pacheco, "Information Visualization: Which Is the Most Appropriate Technique to Represent Data Mining Results?," cimca, pp.1228-1233, 2008 International Conferences on Computational Intelligence for Modelling, Control and Automation; Intelligent Agents, Web Technologies and Internet Commerce; and Innovation in Software Engineering, 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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