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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Handling Large Databases in Data Mining

Handling Large Databases in Data Mining
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Author(s): M. Mehdi Owrang (American University, USA)
Copyright: 2000
Pages: 5
Source title: Challenges of Information Technology Management in the 21st Century
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-878289-84-1.ch012
ISBN13: 9781878289841
EISBN13: 9781466665316


Current database technology involves processing a large volume of data in order to discover new knowledge. The high volume of data makes discovery process computationally expensive. In addition, real-world databases tend to be incomplete, redundant, and inconsistent that could lead to discovering redundant and inconsistent knowledge. We propose to use domain knowledge to reduce the size of the database being considered for discovery and to optimize the hypothesis (representing the pattern to be discovered) by eliminating implied, unnecessary, and redundant conditions from the hypothesis. The benefits can be greater efficiency and the discovery of more meaningful, non-redundant, non-trivial, and consistent rules.

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