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A Comparison and Scenario Analysis of Leading Data Mining Software

A Comparison and Scenario Analysis of Leading Data Mining Software
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Author(s): John Wang (Montclair State University, USA), Xiaohua Hu (Drexel University, USA), Kimberly Hollister (Montclair State University, USA) and Dan Zhu (Iowa State University, USA)
Copyright: 2009
Pages: 19
Source title: Selected Readings on Information Technology Management: Contemporary Issues
Source Author(s)/Editor(s): George Kelley (University of Massachusetts-Boston, USA)
DOI: 10.4018/978-1-60566-092-9.ch012

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Abstract

Finding the right software is often hindered by different criteria as well as by technology changes. We performed an analytic hierarchy process (AHP) analysis using Expert Choice to determine which data mining package was best suitable for us. Deliberating a dozen alternatives and objectives led us to a series of pair-wise comparisons. When further synthesizing the results, Expert Choice helped us provide a clear rationale for the decision. The issue is that data mining technology is changing very rapidly. Our article focused only on the major suppliers typically available in the market place. The method and the process that we have used can be easily applied to analyze and compare other data mining software or knowledge management initiatives.

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