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Efficient Techniques for Decision Support: Approximate Query Processing to Parallel and Value-Based Data Mining - Couverture souple

 
9783639517545: Efficient Techniques for Decision Support: Approximate Query Processing to Parallel and Value-Based Data Mining

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Modern techniques of capturing data have thrown, besides storage, another couple of challenges to the computer scientists, viz. its quick retrieval and efficient processing. Getting the information quickly in today’s ever-increasing data deluge is a key priority for the decision maker. This text examines and describes some new structures and techniques in this area. The purpose of this research is to investigate efficient techniques including data structures, algorithms and their implementations for decision support applications in data warehousing and data mining. The specific techniques proposed include a new efficient indexing structure for approximate query processing, a parallel algorithm for mining frequent patterns, and the mining of value-based itemsets by finding optimal solutions under resource constraints. The effectiveness of each technique has been evaluated using typical test data sets. Written both for computing and information systems researchers, this text is aimed at advanced researchers, particularly, in the area of data warehousing and data mining and, in general, for the database professionals who are keen to know about efficient data organisation.

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Amit Rudra
Edité par Scholars\' Press, 2013
ISBN 10 : 3639517547 ISBN 13 : 9783639517545
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rudra AmitDr Amit Rudra is a lecturer in the School of Information Systems at Curtin University, Australia. He holds a BSc (Hons) in Mathematics and an MSc in Operational Research form University of Delhi, India and a PhD in Compute. N° de réf. du vendeur 151388296

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Amit Rudra
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Modern techniques of capturing data have thrown, besides storage, another couple of challenges to the computer scientists, viz. its quick retrieval and efficient processing. Getting the information quickly in today s ever-increasing data deluge is a key priority for the decision maker. This text examines and describes some new structures and techniques in this area. The purpose of this research is to investigate efficient techniques including data structures, algorithms and their implementations for decision support applications in data warehousing and data mining. The specific techniques proposed include a new efficient indexing structure for approximate query processing, a parallel algorithm for mining frequent patterns, and the mining of value-based itemsets by finding optimal solutions under resource constraints. The effectiveness of each technique has been evaluated using typical test data sets. Written both for computing and information systems researchers, this text is aimed at advanced researchers, particularly, in the area of data warehousing and data mining and, in general, for the database professionals who are keen to know about efficient data organisation. N° de réf. du vendeur 9783639517545

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Amit Rudra
Edité par Scholars' Press Sep 2013, 2013
ISBN 10 : 3639517547 ISBN 13 : 9783639517545
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Modern techniques of capturing data have thrown, besides storage, another couple of challenges to the computer scientists, viz. its quick retrieval and efficient processing. Getting the information quickly in today s ever-increasing data deluge is a key priority for the decision maker. This text examines and describes some new structures and techniques in this area. The purpose of this research is to investigate efficient techniques including data structures, algorithms and their implementations for decision support applications in data warehousing and data mining. The specific techniques proposed include a new efficient indexing structure for approximate query processing, a parallel algorithm for mining frequent patterns, and the mining of value-based itemsets by finding optimal solutions under resource constraints. The effectiveness of each technique has been evaluated using typical test data sets. Written both for computing and information systems researchers, this text is aimed at advanced researchers, particularly, in the area of data warehousing and data mining and, in general, for the database professionals who are keen to know about efficient data organisation. 172 pp. Englisch. N° de réf. du vendeur 9783639517545

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Amit Rudra
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Taschenbuch. Etat : Neu. Neuware -Modern techniques of capturing data have thrown, besides storage, another couple of challenges to the computer scientists, viz. its quick retrieval and efficient processing. Getting the information quickly in today¿s ever-increasing data deluge is a key priority for the decision maker. This text examines and describes some new structures and techniques in this area. The purpose of this research is to investigate efficient techniques including data structures, algorithms and their implementations for decision support applications in data warehousing and data mining. The specific techniques proposed include a new efficient indexing structure for approximate query processing, a parallel algorithm for mining frequent patterns, and the mining of value-based itemsets by finding optimal solutions under resource constraints. The effectiveness of each technique has been evaluated using typical test data sets. Written both for computing and information systems researchers, this text is aimed at advanced researchers, particularly, in the area of data warehousing and data mining and, in general, for the database professionals who are keen to know about efficient data organisation.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch. N° de réf. du vendeur 9783639517545

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Rudra, Amit
Edité par Scholars* Press, 2013
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paperback. Etat : New. New. book. N° de réf. du vendeur ERICA82936395175476

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