Mining fuzzy quantitative association rules

被引：6

作者：

Subramanyam, R. B. V. ^{[1
]}

Goswami, A. ^{[1
]}

机构：

[1] Indian Inst Technol, Dept Math, Kharagpur 721302, W Bengal, India

来源：

EXPERT SYSTEMS | 2006年 / 23卷 / 04期

关键词：

fuzzy association rules; frequent itemsets; fuzzy grids; data mining;

D O I：

10.1111/j.1468-0394.2006.00402.x

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The concept of fuzzy sets is one of the most fundamental and influential tools in the development of computational intelligence. In this paper the fuzzy pincer search algorithm is proposed. It generates fuzzy association rules by adopting combined top-down and bottom-up approaches. A fuzzy grid representation is used to reduce the number of scans of the database and our algorithm trims down the number of candidate fuzzy grids at each level. It has been observed that fuzzy association rules provide more realistic visualization of the knowledge extracted from databases.

引用

页码：212 / 225

页数：14

共 50 条

[21] Mining Fuzzy Multiple-Level Association Rules from Quantitative Data
Tzung-Pei Hong
Kuei-Ying Lin
Been-Chian Chien
Applied Intelligence, 2003, 18 : 79 - 90
[22] Mining fuzzy multiple-level association rules from quantitative data
Hong, TP
Lin, KY
Chien, BC
APPLIED INTELLIGENCE, 2003, 18 (01) : 79 - 90
[23] On the Complexity of Mining Quantitative Association Rules
Jef Wijsen
Robert Meersman
Data Mining and Knowledge Discovery, 1998, 2 : 263 - 281
[24] QuantMiner for Mining Quantitative Association Rules
Salleb-Aouissi, Ansaf
Vrain, Christel
Nortet, Cyril
Kong, Xiangrong
Rathod, Vivek
Cassard, Daniel
JOURNAL OF MACHINE LEARNING RESEARCH, 2013, 14 : 3153 - 3157
[25] On the complexity of mining quantitative association rules
Wijsen, J
Meersman, R
DATA MINING AND KNOWLEDGE DISCOVERY, 1998, 2 (03) : 263 - 281
[26] Fuzzy QMD Algorithm for Mining Fuzzy Association Rules
Wang, Chien-Hua
Lee, Wei-Hsuan
Yeh, Chia-Hsuan
Pang, Chin-Tzong
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON COMMUNICATION AND INFORMATION PROCESSING (ICCIP 2017), 2017, : 50 - 54
[27] A Fuzzy Close Algorithm for Mining Fuzzy Association Rules
Pierrard, Regis
Poli, Jean-Philippe
Hudelot, Celine
INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: THEORY AND FOUNDATIONS, PT II, 2018, 854 : 88 - 99
[28] Quantitative and ordinal association rules mining (QAR mining)
Karel, Filip
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS, 2006, 4251 : 195 - 202
[29] Computationally efficient mining for fuzzy implication-based association rules in quantitative databases
Chen, GQ
Yan, P
Kerre, EE
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2004, 33 (2-3) : 163 - 182
[30] A new algorithm for mining fuzzy association rules
Gao, Y
Ma, J
Ma, L
PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 1635 - 1640

← 1 2 3 4 5 →