Fast distributed algorithm for mining association rules

David W. Cheung; Jiawei Han; Vincent To Yee Ng; Ada W. Fu; Yongjian Fu

Fast distributed algorithm for mining association rules

David W. Cheung, Jiawei Han, Vincent To Yee Ng, Ada W. Fu, Yongjian Fu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

321 Citations (Scopus)

Abstract

With 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 investigate efficient 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.

Original language	English
Title of host publication	Parallel and Distributed Information Systems - Proceedings of the International Conference
Publisher	IEEE
Pages	31-42
Number of pages	12
Publication status	Published - 1 Dec 1996
Externally published	Yes
Event	Proceedings of the 1996 4th International Conference on Parallel and Distributed Information Systems - Miami Beach, FL, United States Duration: 18 Dec 1996 → 20 Dec 1996

Conference

Conference	Proceedings of the 1996 4th International Conference on Parallel and Distributed Information Systems
Country/Territory	United States
City	Miami Beach, FL
Period	18/12/96 → 20/12/96

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{763f962b3f6b4b08b2629a51ad886326,

title = "Fast distributed algorithm for mining association rules",

abstract = "With 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 investigate efficient 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.",

author = "Cheung, {David W.} and Jiawei Han and Ng, {Vincent To Yee} and Fu, {Ada W.} and Yongjian Fu",

year = "1996",

month = dec,

day = "1",

language = "English",

pages = "31--42",

booktitle = "Parallel and Distributed Information Systems - Proceedings of the International Conference",

publisher = "IEEE",

address = "United States",

note = "Proceedings of the 1996 4th International Conference on Parallel and Distributed Information Systems ; Conference date: 18-12-1996 Through 20-12-1996",

}

Fast distributed algorithm for mining association rules. / Cheung, David W.; Han, Jiawei; Ng, Vincent To Yee et al.
Parallel and Distributed Information Systems - Proceedings of the International Conference. IEEE, 1996. p. 31-42.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Fast distributed algorithm for mining association rules

AU - Cheung, David W.

AU - Han, Jiawei

AU - Ng, Vincent To Yee

AU - Fu, Ada W.

AU - Fu, Yongjian

PY - 1996/12/1

Y1 - 1996/12/1

N2 - With 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 investigate efficient 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.

AB - With 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 investigate efficient 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.

UR - http://www.scopus.com/inward/record.url?scp=0030387678&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SP - 31

EP - 42

BT - Parallel and Distributed Information Systems - Proceedings of the International Conference

PB - IEEE

T2 - Proceedings of the 1996 4th International Conference on Parallel and Distributed Information Systems

Y2 - 18 December 1996 through 20 December 1996

ER -

Fast distributed algorithm for mining association rules

Abstract

Conference

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this