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Title:
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QUALITY EVALUATION OF VISUAL DATA MINING TOOLS |
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Author(s):
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Edwige Fangseu Badjio |
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ISBN:
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972-99353-6-X |
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Editors:
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Nuno Guimarães and Pedro Isaías |
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Year:
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2005 |
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Edition:
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2 |
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Keywords:
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HCI, software quality, visual data mining, usability, utility, acceptability. |
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Type:
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Short Paper |
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First Page:
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133 |
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Last Page:
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138 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This work presents a methodology allowing the analysis and the evaluation of the utility and usability of visual data mining tools. Several knowledge discoveries in database packages offer means to visualize and mine data, but none have shown the quality of those tools. Our analysis method concerns a set of measures that could be used to obtain the quality of visual data mining applications. The theoretical fundaments of this method are the works of data mining, human machine interfaces, data visualization, visual data mining and cognitive psychology fields. We have defined six analysis topics that are represented in a tree structure including the principal topics, under topics or meta-criteria and the criteria. For the illustration of our approach, we present a case study aiming to evaluate UserClassifier, a module within WEKA [Weka, 2004]. |
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