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Data Mining Process

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Uncertainty Handling and Quality Assessment in Data Mining

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

Abstract

The knowledge discovery from large data repositories has been accepted as a key research issue in the field of databases, machine learning, and statistics, as well as an important opportunity for innovation in business. Various applications, such as data warehousing and on-line services via the Internet, invoke different data mining techniques in order to achieve better understanding of customers’ behavior and thus to improve the quality of provided services achieving their business advantage.

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Authors and Affiliations

  1. Department of Informatics, Athens University of Economics and Business, Greece

    Michalis Vazirgiannis PhD & Maria Halkidi MSc

  2. Department of Computer Science and Engineering, University of California, Riverside, USA

    Dimitrios Gunopulos PhD

Authors
  1. Michalis Vazirgiannis PhD
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  2. Maria Halkidi MSc
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  3. Dimitrios Gunopulos PhD
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Vazirgiannis, M., Halkidi, M., Gunopulos, D. (2003). Data Mining Process. In: Uncertainty Handling and Quality Assessment in Data Mining. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-0031-7_2

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  • DOI: https://doi.org/10.1007/978-1-4471-0031-7_2

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