Systems for knowledge discovery in databases
IEEE Transactions on Knowledge and Data EngineeringPublished 1 January 1993
Christopher J. Matheus, Philip K. Chan, Gregory Piatetsky-Shapiro
Citations257
SJR quartileQ1
SJR score2.57
SNIP3.30
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TL;DR
A model of an idealized knowledge-discovery system is presented as a reference for studying and designing new systems and is used in the comparison of three systems: CoverStory, EXPLORA, and the Knowledge Discovery Workbench.
Abstract
Knowledge-discovery systems face challenging problems from real-world databases, which tend to be dynamic, incomplete, redundant, noisy, sparse, and very large. These problems are addressed and some techniques for handling them are described. A model of an idealized knowledge-discovery system is presented as a reference for studying and designing new systems. This model is used in the comparison of three systems: CoverStory, EXPLORA, and the Knowledge Discovery Workbench. The deficiencies of existing systems relative to the model reveal several open problems for future research.>
Keywords
Computer Science
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