Evaluation of Usability Aspects in Data Mining Tools

Abstract


Currently several techniques and tools are proposed to allow the end user to interpret large volumes of data stored in organizational databases for a particular decision making. In this work, we discuss ways of interacting with cluster analysis tools, taking into account both clustering and interpretation steps. We investigate how usability and user experience in such tools can improve understanding of discovered knowledge and thus improve decision making over a database. Four different cluster analysis tools were evaluated: Knime, Orange Canvas, Rapidminer Studio and Weka data mining tools.
Keywords: Ferramentas para Mineração de Dados, Análise de cluster, Usabilidade
Published
2014-11-03
How to Cite

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BOSCARIOLI, Clodis; VITERBO, José; TEIXEIRA, Mateus Felipe. Evaluation of Usability Aspects in Data Mining Tools. In: REGIONAL SCHOOL ON INFORMATION SYSTEMS OF RIO DE JANEIRO (ERSI-RJ), 1. , 2014, Niterói. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2014 . p. 87-94.