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Knowledge discovery in databases: Progress report

Published online by Cambridge University Press:  07 July 2009

Gregory Piatetsky-Shapiro
Gregory Piatetsky-Shapiro
Affiliation:
GTE Laboratories Incorporated, 40 Sylvan Road, Waltham, MA 01254USA (email: [email protected])
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Extract

As the number and size of very large databases continues to grow rapidly, so does the need to make sense of them. This need is addressed by the field called knowledge Discovery in Databases (KDD), which combines approaches from machine learning, statistics, intelligent databases, and knowledge acquisition. KDD encompasses a number of different discovery methods, such as clustering, data summarization, learning classification rules, finding dependency networks, analysing changes, and detecting anomalies (Matheus et at., 1993).

Type
Research Article
Information
The Knowledge Engineering Review , Volume 9 , Issue 1 , March 1994 , pp. 57 - 60
Copyright
Copyright © Cambridge University Press 1994

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References

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