This book provides a unique and fairly comprehensive treatment of a popular data mining task known as “association rule mining.” At the heart of this book, a vertical framework (based on the patented P-tree technology along with other well-known artificial intelligence techniques) for data representation and data mining is described. The framework is adapted to environments that require “divide and conquer” parallel processing or pruning beyond the ubiquitous support-based pruning. Along with the theory, the book highlights the versatility of the presented framework in different application domains ranging from citation analysis to precision agriculture and bioinformatics.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This book provides a unique and fairly comprehensive treatment of a popular data mining task known as “association rule mining.” At the heart of this book, a vertical framework (based on the patented P-tree technology along with other well-known artificial intelligence techniques) for data representation and data mining is described. The framework is adapted to environments that require “divide and conquer” parallel processing or pruning beyond the ubiquitous support-based pruning. Along with the theory, the book highlights the versatility of the presented framework in different application domains ranging from citation analysis to precision agriculture and bioinformatics.
Dr. Rahal is an Assistant Prof. of Computer Science at the College of St. Benedict and St. John''s Univ. He has a Ph.D. and an M.S. from North Dakota State Univ. Dr. Perrizo is a Distinguished Prof. of Computer Science at North Dakota State Univ. He holds a Ph.D. from the Univ. of Minnesota and an M.S. from the Univ. of Wisconsin.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Vertical Association Rule Mining | From Data Representation to Data Mining | Imad Rahal | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639083019 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101708352
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a unique and fairly comprehensive treatment of a popular data mining task known as association rule mining. At the heart of this book, a vertical framework (based on the patented P-tree technology along with other well-known artificial intelligence techniques) for data representation and data mining is described. The framework is adapted to environments that require divide and conquer parallel processing or pruning beyond the ubiquitous support-based pruning. Along with the theory, the book highlights the versatility of the presented framework in different application domains ranging from citation analysis to precision agriculture and bioinformatics.; This work focuses on the data-mining task of association rule mining which discovers association relationships among items in datasets matching user-defined measures of interest. We describe an efficient vertical framework for representing data and mining frequent itemsets that is based on the P-tree technology along with other artificial intelligence techniques, such as set-enumeration trees and tabu search. With the objective of handling the mounting needs of many applications, such as precision agriculture, the proposed framework is used to produce rules in situations where the ubiquitous support-based pruning is not sought. In the context of citation graphs, our proposed framework operates in a (semi) divide-and-conquer parallelized fashion, to discover patterns among subject matters that reveal the evolution history and any possible future extensions of subject matters. The same framework is utilized in an interactive incremental parallel model which focuses on analyzing genome annotation data for association rules potentially useful in annotating new genes, replacing missing values, and validating old annotations. N° de réf. du vendeur 9783639083019
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 132 pages. 8.66x5.91x0.30 inches. In Stock. N° de réf. du vendeur __3639083016
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 132 pages. 8.66x5.91x0.30 inches. In Stock. N° de réf. du vendeur 3639083016
Quantité disponible : 1 disponible(s)