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

Contributor(s): Zaki, Mohammed J [editor.] | Ho, Ching-Tien [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer Science ; 1759Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2000Description: VIII, 260 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540465027Subject(s): Computer science | Computer Communication Networks | Computer software | Information storage and retrieval systems | Information systems | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Information Storage and Retrieval | Computer Communication Networks | Algorithm Analysis and Problem Complexity | Information Systems Applications (incl.Internet)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 LOC classification: Q334-342TJ210.2-211.495Online resources: Click here to access online
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.
In: Springer eBooks
Item type: E-BOOKS
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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.

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