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The KDD process for extracting useful knowledge from volumes of data

Communications of the ACM · 1996 · Vol. 39(11) · pp. 27–34
Usama M. FayyadGregory Piatetsky-ShapiroPadhraic Smyth

Abstract

article Free Access Share on The KDD process for extracting useful knowledge from volumes of data Authors: Usama Fayyad Jet Propulsion Laboratory, California Institute of Technology Jet Propulsion Laboratory, California Institute of TechnologyView Profile , Gregory Piatetsky-Shapiro GTE Laboratories GTE LaboratoriesView Profile , Padhraic Smyth University of California, Irvine and Jet Propulsion Laboratory, California Institute of Technology University of California, Irvine and Jet Propulsion Laboratory, California Institute of TechnologyView Profile Authors Info & Claims Communications of the ACMVolume 39Issue 11Nov. 1996pp 27–34https://doi.org/10.1145/240455.240464Published:01 November 1996Publication History 1,074citation15,552DownloadsMetricsTotal Citations1,074Total Downloads15,552Last 12 Months2,325Last 6 weeks471 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Bayesian Modeling and Causal InferenceData Quality and ManagementAdvanced Database Systems and QueriesJet propulsionCitationPropulsionComputer scienceProcess (computing)AeronauticsLibrary scienceEngineeringOperating systemAerospace engineering
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References
Advances in knowledge discovery and data mining
Computers & Mathematics with Applications · 1996 · 2,977 citations
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The KDD process for extracting useful knowledge from volumes of data · Scinovex