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Advances in Data Mining. Applications and Theoretical Aspects [electronic resource] : 12th Industrial Conference, ICDM 2012, Berlin, Germany, July 13-20, 2012. Proceedings / edited by Petra Perner.

Contributor(s): Perner, Petra [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Artificial Intelligence: 7377Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Edition: 1st ed. 2012.Description: XI, 289 p. 97 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642314889.Subject(s): Data mining | Multimedia systems | Computer vision | Application software | Database management | Artificial intelligence | Data Mining and Knowledge Discovery | Multimedia Information Systems | Computer Vision | Computer and Information Systems Applications | Database Management | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.312 Online resources: Click here to access online In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.
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This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.

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