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• catalog abstract "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.".
• catalog contributor b11701343.
• catalog contributor b11701344.
• catalog created "2000.".
• catalog date "2000".
• catalog date "2000.".
• catalog dateCopyrighted "2000.".
• catalog description "Includes bibliographical references and index.".
• catalog description "Parallel and distributed data mining : an introduction / Mohammed J. Zaki -- The integrated delivery of large-scale data mining : the ACSys data mining project / Graham Williams [and others] -- A high performance implementation of the data space transfer protocol (DSTP) / Stuart Bailey [and others] -- Active mining in a distributed setting / Srinivasan Parthasarathy, Sandhya Dwarkadas, and Mitsunori Ogihara -- Efficient parallel algorithms for mining associations / Mahesh V. Joshi [and others] -- Parallel branch-and-bound graph search for correlated association rules / Shinichi Morishita and Akihiro Nakaya -- Parallel generalized association rule mining on large scale PC cluster / Takahiko Shintani and Masaru Kitsuregawa -- Parallel sequence mining on shared-memory machines / Mohammed J. Zaki -- Parallel predictor generation / D.B. Skillicorn -- Efficient parallel classification using dimensional aggregates / Sanjay Goil and Alok Choudhary -- Learning rules from distributed data / Lawrence O. Hall [and others] -- Collective, hierarchical clustering from distributed, heterogeneous data / Erik L. Johnson and Hillol Kargupta -- A data-clustering algorithm on distributed memory multiprocessors / Inderjit S. Dhillon and Dharmendra S. Modha.".
• catalog description "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.".
• catalog extent "viii, 260 p. :".
• catalog identifier "3540671943 (alk. paper)".
• catalog isPartOf "Lecture notes in computer science ; 1759. Lecture notes in artificial intelligence".
• catalog isPartOf "Lecture notes in computer science ; 1759.".
• catalog isPartOf "Lecture notes in computer science. Lecture notes in artificial intelligence.".
• catalog issued "2000".
• catalog issued "2000.".
• catalog language "eng".
• catalog publisher "Berlin ; New York : Springer,".
• catalog subject "006.3 21".
• catalog subject "Artificial intelligence.".
• catalog subject "Computer Communication Networks.".
• catalog subject "Computer science.".
• catalog subject "Computer software.".
• catalog subject "Data mining.".
• catalog subject "Information storage and retrieval systems.".
• catalog subject "Information systems.".
• catalog subject "Parallel processing (Electronic computers)".
• catalog subject "Parallel processing (Electronic processing)".
• catalog subject "QA76.9.D343 L37 2000".
• catalog tableOfContents "Parallel and distributed data mining : an introduction / Mohammed J. Zaki -- The integrated delivery of large-scale data mining : the ACSys data mining project / Graham Williams [and others] -- A high performance implementation of the data space transfer protocol (DSTP) / Stuart Bailey [and others] -- Active mining in a distributed setting / Srinivasan Parthasarathy, Sandhya Dwarkadas, and Mitsunori Ogihara -- Efficient parallel algorithms for mining associations / Mahesh V. Joshi [and others] -- Parallel branch-and-bound graph search for correlated association rules / Shinichi Morishita and Akihiro Nakaya -- Parallel generalized association rule mining on large scale PC cluster / Takahiko Shintani and Masaru Kitsuregawa -- Parallel sequence mining on shared-memory machines / Mohammed J. Zaki -- Parallel predictor generation / D.B. Skillicorn -- Efficient parallel classification using dimensional aggregates / Sanjay Goil and Alok Choudhary -- Learning rules from distributed data / Lawrence O. Hall [and others] -- Collective, hierarchical clustering from distributed, heterogeneous data / Erik L. Johnson and Hillol Kargupta -- A data-clustering algorithm on distributed memory multiprocessors / Inderjit S. Dhillon and Dharmendra S. Modha.".
• catalog title "Large scale parallel data mining / Mohammed J. Zaki, Ching-Tien Ho (eds.).".
• catalog type "Kongress. swd".
• catalog type "text".