Mining fuzzy association rules

Chun Chung Chan; Wai Ho Au

Mining fuzzy association rules

Chun Chung Chan, Wai Ho Au

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

153 Citations (Scopus)

Abstract

A technique called F-APACS which employs linguistic terms to represent the revealed regularities and exceptions for mining fuzzy association rules is presented. The linguistic representation is useful when the rules discovered are presented to human experts for examination. The definition of the linguistic terms is based on fuzzy set theory and the rules having these terms are called fuzzy association rules. The use of fuzzy techniques is considered as one of the key components of data mining systems because of the affinity with the human knowledge representation.

Original language	English
Title of host publication	International Conference on Information and Knowledge Management, Proceedings
Publisher	ACM
Pages	209-215
Number of pages	7
Publication status	Published - 1 Dec 1997
Event	Proceedings of the 1997 6th International Conference on Information and Knowledge Management, CIKM'97 - Las Vegas, NV, United States Duration: 10 Nov 1997 → 14 Nov 1997

Conference

Conference	Proceedings of the 1997 6th International Conference on Information and Knowledge Management, CIKM'97
Country/Territory	United States
City	Las Vegas, NV
Period	10/11/97 → 14/11/97

ASJC Scopus subject areas

General Business,Management and Accounting

Cite this

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title = "Mining fuzzy association rules",

abstract = "A technique called F-APACS which employs linguistic terms to represent the revealed regularities and exceptions for mining fuzzy association rules is presented. The linguistic representation is useful when the rules discovered are presented to human experts for examination. The definition of the linguistic terms is based on fuzzy set theory and the rules having these terms are called fuzzy association rules. The use of fuzzy techniques is considered as one of the key components of data mining systems because of the affinity with the human knowledge representation.",

author = "Chan, {Chun Chung} and Au, {Wai Ho}",

year = "1997",

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day = "1",

language = "English",

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booktitle = "International Conference on Information and Knowledge Management, Proceedings",

publisher = "ACM",

note = "Proceedings of the 1997 6th International Conference on Information and Knowledge Management, CIKM'97 ; Conference date: 10-11-1997 Through 14-11-1997",

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T1 - Mining fuzzy association rules

AU - Chan, Chun Chung

AU - Au, Wai Ho

PY - 1997/12/1

Y1 - 1997/12/1

N2 - A technique called F-APACS which employs linguistic terms to represent the revealed regularities and exceptions for mining fuzzy association rules is presented. The linguistic representation is useful when the rules discovered are presented to human experts for examination. The definition of the linguistic terms is based on fuzzy set theory and the rules having these terms are called fuzzy association rules. The use of fuzzy techniques is considered as one of the key components of data mining systems because of the affinity with the human knowledge representation.

AB - A technique called F-APACS which employs linguistic terms to represent the revealed regularities and exceptions for mining fuzzy association rules is presented. The linguistic representation is useful when the rules discovered are presented to human experts for examination. The definition of the linguistic terms is based on fuzzy set theory and the rules having these terms are called fuzzy association rules. The use of fuzzy techniques is considered as one of the key components of data mining systems because of the affinity with the human knowledge representation.

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M3 - Conference article published in proceeding or book

SP - 209

EP - 215

BT - International Conference on Information and Knowledge Management, Proceedings

PB - ACM

T2 - Proceedings of the 1997 6th International Conference on Information and Knowledge Management, CIKM'97

Y2 - 10 November 1997 through 14 November 1997

ER -

Mining fuzzy association rules

Abstract

Conference

ASJC Scopus subject areas

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