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Conference Paper: A fast distributed algorithm for mining association rules

TitleA fast distributed algorithm for mining association rules
Authors
KeywordsComputers
Computer architecture
Issue Date1996
PublisherIEEE.
Citation
The 4th International Conference on Parallel and Distributed Systems, Miami Beach, FL., 18-20 December 1996. In International Conference on Parallel and Distributed Systems Proceedings, 1996, p. 31-42 How to Cite?
AbstractWith the existence of many large transaction databases, the huge amounts of data, the high scalability of distributed systems, and the easy partition and distribution of a centralized database, it is important to inuestzgate eficient methods for distributed mining of association rules. This study discloses some interesting relationships between locally large and globally large itemsets and proposes an interesting distributed association rule mining algorithm, FDM (Fast Distributed Mining of association rules), which generates a small number of candidate sets and substantially reduces the number of messages to be passed at mining association rules. Our performance study shows that FDM has a superior performance over the direct application of a typical sequential algorithm. Further performance enhancement leads to a few variations of the algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/45576
ISSN

 

DC FieldValueLanguage
dc.contributor.authorCheung, DWLen_HK
dc.contributor.authorHan, Jen_HK
dc.contributor.authorNg, VTen_HK
dc.contributor.authorFu, AWen_HK
dc.contributor.authorFu, Yen_HK
dc.date.accessioned2007-10-30T06:29:33Z-
dc.date.available2007-10-30T06:29:33Z-
dc.date.issued1996en_HK
dc.identifier.citationThe 4th International Conference on Parallel and Distributed Systems, Miami Beach, FL., 18-20 December 1996. In International Conference on Parallel and Distributed Systems Proceedings, 1996, p. 31-42en_HK
dc.identifier.issn1521-9097en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45576-
dc.description.abstractWith the existence of many large transaction databases, the huge amounts of data, the high scalability of distributed systems, and the easy partition and distribution of a centralized database, it is important to inuestzgate eficient methods for distributed mining of association rules. This study discloses some interesting relationships between locally large and globally large itemsets and proposes an interesting distributed association rule mining algorithm, FDM (Fast Distributed Mining of association rules), which generates a small number of candidate sets and substantially reduces the number of messages to be passed at mining association rules. Our performance study shows that FDM has a superior performance over the direct application of a typical sequential algorithm. Further performance enhancement leads to a few variations of the algorithm.en_HK
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofInternational Conference on Parallel and Distributed Systems Proceedings-
dc.rights©1996 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectComputersen_HK
dc.subjectComputer architectureen_HK
dc.titleA fast distributed algorithm for mining association rulesen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1521-9097&volume=&spage=31&epage=42&date=1996&atitle=A+fast+distributed+algorithm+for+mining+association+rulesen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/PDIS.1996.568665en_HK
dc.identifier.hkuros26205-

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