Articles liés à Data Analysis and Pattern Recognition in Multiple Databases
Synopsis
Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.
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Présentation de l'éditeur
This book presents an influence analysis between items in time-stamped databases. It covers developments in data analysis and pattern recognition in multiple databases and details the application of intelligent systems modeling to multiple database analysis.
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- ÉditeurSpringer International Publishing AG
- Date d'édition2013
- ISBN 10 331903409X
- ISBN 13 9783319034096
- ReliureRelié
- Langueanglais
- Nombre de pages238
- Coordonnées du fabricantnon disponible
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Data Analysis and Pattern Recognition in Multiple Databases
Edité par
Springer International Publishing, 2013
ISBN 10 : 331903409X
ISBN 13 : 9783319034096
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Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Sonstiges. N° de réf. du vendeur 24395627/2
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Data Analysis and Pattern Recognition in Multiple Databases
Edité par
Springer International Publishing, 2013
ISBN 10 : 331903409X
ISBN 13 : 9783319034096
Ancien ou d'occasion
Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Sonstiges. N° de réf. du vendeur 24395627/12
Quantité disponible : 1 disponible(s)
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Data Analysis and Pattern Recognition in Multiple Databases
Edité par
Springer International Publishing, 2013
ISBN 10 : 331903409X
ISBN 13 : 9783319034096
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research on Data Analysis and Pattern Recognition in Multiple DatabasesApplication of Intelligent Systems Modeling to Multiple Database AnalysisWritten by experts in the fieldRecent research on Data Analysis and Pattern Re. N° de réf. du vendeur 4496674
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DATA ANALYSIS AND PATTERN RECOGNITION IN MULTIPLE DATABASES VOL 61 (HB 2014)
Vendeur : Basi6 International, Irving, TX, Etats-Unis
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Etat : Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. N° de réf. du vendeur ABEJUNE24-405113
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Data Analysis and Pattern Recognition in Multiple Databases
Edité par
Springer International Publishing, 2013
ISBN 10 : 331903409X
ISBN 13 : 9783319034096
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments. N° de réf. du vendeur 9783319034096
Quantité disponible : 1 disponible(s)
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Data Analysis and Pattern Recognition in Multiple Databases
Edité par
Springer International Publishing Dez 2013, 2013
ISBN 10 : 331903409X
ISBN 13 : 9783319034096
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments. 256 pp. Englisch. N° de réf. du vendeur 9783319034096
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Data Analysis and Pattern Recognition in Multiple Databases
ISBN 10 : 331903409X
ISBN 13 : 9783319034096
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. Neuware -Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 256 pp. Englisch. N° de réf. du vendeur 9783319034096
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Data Analysis and Pattern Recognition in Multiple Databases
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Data Analysis and Pattern Recognition in Multiple Databases
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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