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Large-Scale Parallel Data Mining : Lecture Notes in Artificial Intelligence - Mohammed J. Zaki

Large-Scale Parallel Data Mining

Lecture Notes in Artificial Intelligence

By: Mohammed J. Zaki (Editor), Ching-Tien Ho (Editor)

Paperback Published: 23rd February 2000
ISBN: 9783540671947
Number Of Pages: 260

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Withthe unprecedented rate at which data is being collected today in almostall elds of human endeavor, there is an emerging economic and scientic need to extract useful information from it. For example, many companies already have data-warehouses inthe terabyte range (e.g., FedEx, Walmart).The WorldWide Web has an estimated 800 millionweb-pages. Similarly, scienti c data is rea- ing gigantic proportions (e.g., NASA space missions, Human Genome Project). High-performance, scalable, parallel, and distributed computing is crucial for ensuring system scalabilityand interactivityas datasets continue to grow in size and complexity. Toaddress thisneedweorganizedtheworkshoponLarge-ScaleParallelKDD Systems, which was held in conjunction with the 5th ACM SIGKDD Inter- tional Conference on Knowledge Discovery and Data Mining, on August 15th, 1999, San Diego, California. The goal of this workshop was to bring researchers and practitioners together in a setting where they could discuss the design, - plementation, anddeploymentoflarge-scaleparallelknowledgediscovery (PKD) systems, which can manipulate data taken from very large enterprise or sci- tic databases, regardless of whether the data is located centrally or is globally distributed. Relevant topics identie d for the workshop included: { How to develop a rapid-response, scalable, and parallel knowledge discovery system that supports global organizations with terabytes of data.

Large-Scale Parallel Data Mining
Parallel and Distributed Data Mining: An Introductionp. 1
Mining Frameworks
The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Projectp. 24
A High Performance Implementation of the Data Space Transfer Protocol (DSTP)p. 55
Active Mining in a Distributed Settingp. 65
Associations and Sequences
Efficient Parallel Algorithms for Mining Associationsp. 83
Parallel Branch-and-Bound Graph Search for Correlated Association Rulesp. 127
Parallel Generalized Association Rule Mining on Large Scale PC Clusterp. 145
Parallel Sequence Mining on Shared-Memory Machinesp. 161
Classification
Parallel Predictor Generationp. 190
Efficient Parallel Classification Using Dimensional Aggregatesp. 197
Learning Rules from Distributed Datap. 211
Clustering
Collective, Hierarchical Clustering from Distributed, Heterogeneous Datap. 221
A Data-Clustering Algorithm On Distributed Memory Multiprocessorsp. 245
Author Indexp. 261
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9783540671947
ISBN-10: 3540671943
Series: Lecture Notes in Artificial Intelligence
Audience: General
Format: Paperback
Language: English
Number Of Pages: 260
Published: 23rd February 2000
Publisher: SPRINGER VERLAG GMBH
Country of Publication: DE
Dimensions (cm): 23.39 x 15.6  x 1.47
Weight (kg): 0.39

Earn 222 Qantas Points
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