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Knowledge Discovery and Data Mining

  • Chapter
Handbook on Knowledge Management

Part of the book series: International Handbooks on Information Systems ((INFOSYS,volume 2))

Abstract

With the advances of information technology and widespread diffusion of databases systems in organizations, large volumes of data are generated and collected by organizations. This dramatic expansion of data has generated an urgent need for new analysis techniques that can intelligently and automatically transform the processed data into useful information and knowledge. As a result, knowledge discovery and data mining have increased in importance and economic value. Knowledge discovery refers to the overall process of discovering useful knowledge from data, while data mining refers to the extraction of patterns from data. This chapter provides a reasonably comprehensive review of knowledge discovery and its associated data mining techniques. Based on the kinds of knowledge that can be discovered in databases, data mining techniques can be broadly structured into several categories, including classification, clustering, dependency analysis, data visualization, and text mining. Representative data mining techniques for each category are depicted in this chapter.

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Authors and Affiliations

  1. Department of Information Management, National Sun Yat-Sen University, Kaohsiung, Taiwan

    Chih-Ping Wei

  2. Department of Decision and Information Sciences, University of Florida, Gainesville, FL, USA

    Selwyn Piramuthu

  3. Department of Business Administration and Beckman Institute for Advanced Sciences and Technology, University of Illinois, Urbana, IL, USA

    Michael J. Shaw

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  1. Chih-Ping Wei
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  2. Selwyn Piramuthu
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  3. Michael J. Shaw
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Editors and Affiliations

  1. Rosenthal Endowed Chair in Management Information Systems, University of Kentucky, 425B Gatton Building of Business and Economics, 40506-0034, Lexington, KY, USA

    Clyde W. Holsapple

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Wei, CP., Piramuthu, S., Shaw, M.J. (2003). Knowledge Discovery and Data Mining. In: Holsapple, C.W. (eds) Handbook on Knowledge Management. International Handbooks on Information Systems, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24748-7_9

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