Data Mining in Public Administration

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Author(s): John Wang (Montclair State University, USA), Xiaohua Hu (Drexel University, USA)and Dan Zhu (Iowa State University, USA)
Copyright: 2008
Pages: 12
Source title: Handbook of Research on Public Information Technology
Source Author(s)/Editor(s): G. David Garson (North Carolina State University, USA)and Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-857-4.ch051

Keywords: Electronic Government / Government & Law / Information Science Reference

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Abstract

Data mining involves searching through databases for potentially useful information such as knowledge rules, patterns, regularities, and other trends hidden in the data. In order to complete these tasks, the contemporary data mining packages offer techniques such as neural networks, inductive learning decision trees, cluster analysis, link analysis, genetic algorithms, visualization, and so forth (Hand, Mannila, & Smyth, 2001; Wang, 2006). In general, data mining is a data analytical technique that assists businesses in learning and understanding their customers so that decisions and strategies can be implemented most accurately and effectively to maximize profitability. Data mining is not general data analysis, but a comprehensive technique that requires analytical skills, information construction, and professional knowledge.

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