Syndetics cover image
Image from Syndetics

Large-Scale Parallel Data Mining [electronic resource] / edited by Mohammed J. Zaki, Ching-Tien Ho.

Contributor(s): Material type: TextSeries: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2000Edition: 1st ed. 2000Description: VIII, 260 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540465027
Subject(s): DDC classification:
  • 006.3 23
Online resources:
Contents:
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.
No physical items for this record

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.

Licensed e-book