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.
By: Perner, Petra [editor.].
Contributor(s): SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 7377Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Description: XI, 289 p. 97 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642314889.Subject(s): Computer science | Database management | Data mining | Multimedia systems | Artificial intelligence | Computer vision | Computer Science | Data Mining and Knowledge Discovery | Multimedia Information Systems | Image Processing and Computer Vision | Information Systems Applications (incl. Internet) | Database Management | Artificial Intelligence (incl. Robotics)DDC classification: 006.312 Online resources: Click here to access online
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Springer eBooksSummary: 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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