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Large-Scale Parallel Data Mining: Lecture Notes in Computer Science, cartea 1759

Editat de Mohammed J. Zaki, Ching-Tien Ho
en Limba Engleză Paperback – 23 feb 2000

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Specificații

ISBN-13: 9783540671947
ISBN-10: 3540671943
Pagini: 272
Ilustrații: VIII, 260 p.
Dimensiuni: 155 x 233 x 14 mm
Greutate: 0.39 kg
Ediția:2000
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Large-Scale Parallel Data Mining.- Parallel and Distributed Data Mining: An Introduction.- Mining Frameworks.- The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project.- A High Performance Implementation of the Data Space Transfer Protocol (DSTP).- Active Mining in a Distributed Setting.- Associations and Sequences.- Efficient Parallel Algorithms for Mining Associations.- Parallel Branch-and-Bound Graph Search for Correlated Association Rules.- Parallel Generalized Association Rule Mining on Large Scale PC Cluster.- Parallel Sequence Mining on Shared-Memory Machines.- Classification.- Parallel Predictor Generation.- Efficient Parallel Classification Using Dimensional Aggregates.- Learning Rules from Distributed Data.- Clustering.- Collective, Hierarchical Clustering from Distributed, Heterogeneous Data.- A Data-Clustering Algorithm on Distributed Memory Multiprocessors.

Caracteristici

Includes supplementary material: sn.pub/extras