Inductive learning algorithms and representations for text categorization
Published 1 November 1998
Susan Dumais, John Platt, David Heckerman, Mehran Sahami
Citations1,465
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A comparison of the effectiveness of five different automatic learning algorithms for text categorization in terms of learning speed, realtime classification speed, and classification accuracy is compared.
Abstract
Article Inductive learning algorithms and representations for text categorization Share on Authors: Susan Dumais Microsoft Research, One Microsoft way, Redmond, WA Microsoft Research, One Microsoft way, Redmond, WAView Profile , John Platt Microsoft Research, One Microsoft way, Redmond, WA Microsoft Research, One Microsoft way, Redmond, WAView Profile , David Heckerman Microsoft Research, One Microsoft way, Redmond, WA Microsoft Research, One Microsoft way, Redmond, WAView Profile , Mehran Sahami Computer Science Department, Standford University, Standford, CA Computer Science Department, Standford University, Standford, CAView Profile Authors Info & Claims CIKM '98: Proceedings of the seventh international conference on Information and knowledge managementNovember 1998 Pages 148–155https://doi.org/10.1145/288627.288651Published:01 November 1998 797citation4,668DownloadsMetricsTotal Citations797Total Downloads4,668Last 12 Months142Last 6 weeks21 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 SiteGet Access
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