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International Journal of General Systems Volume 33, 2004 - Issue 2-3: Information Fusion
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Original Articles

Computationally Efficient Mining for Fuzzy Implication-Based Association Rules in Quantitative Databases

Guoqing Chen School of Economics and Management, Tsinghua University, 100084, Beijing, ChinaCorrespondence[email protected]
,
Peng Yan School of Economics and Management, Tsinghua University, 100084, Beijing, China
&
Etienne E. Kerre Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281/S9, 9000, Gent, Belgium
Pages 163-182 | Received 15 Jan 2003, Accepted 19 May 2003, Published online: 26 Jan 2007

Citations (17)

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Zuoliang Chen & Guoqing Chen. (2008) Building an Associative Classifier Based on Fuzzy Association Rules. International Journal of Computational Intelligence Systems 1:3, pages 262-273.
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Articles from other publishers (16)

Mehfooza Munavar Basha & P. Kuppusamy. 2023. Advances in Communication, Devices and Networking. Advances in Communication, Devices and Networking 283 296 .
M. Mehfooza & Haroon Basha I. (2021) An automated prescriptive domain data preprocessing algorithm to support multilabel‐multicriteria classification for Indian coastal dataset, crop dataset, and breast cancer dataset. International Journal of Communication Systems.
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Yi Chai, Guixia Kang, Ningbo Zhang, Yanyan Guo & Jingning Wang. (2015) An Associative Classifier Adopting Fuzzy Weighted Rules Based on Information Gain. An Associative Classifier Adopting Fuzzy Weighted Rules Based on Information Gain.
Wu Jian & Li Xing-ming. (2011) Mining multidimensional fuzzy association rules of alarms in communication networks. Mining multidimensional fuzzy association rules of alarms in communication networks.
Ashish Mangalampalli & Vikram Pudi. (2010) FPrep: Fuzzy clustering driven efficient automated pre-processing for fuzzy association rule mining. FPrep: Fuzzy clustering driven efficient automated pre-processing for fuzzy association rule mining.
Ashish Mangalampalli & Vikram Pudi. (2010) FACISME: Fuzzy associative classification using iterative scaling and maximum entropy. FACISME: Fuzzy associative classification using iterative scaling and maximum entropy.
Ashish Mangalampalli & Vikram Pudi. (2009) Fuzzy association rule mining algorithm for fast and efficient performance on very large datasets. Fuzzy association rule mining algorithm for fast and efficient performance on very large datasets.
Ming Ren, Zuoliang Chen, Chuanlan Liu & Guoqing Chen. (2008) An Evolving Information System Based on Data Mining Knowledge to Support Customer Relationship Management. An Evolving Information System Based on Data Mining Knowledge to Support Customer Relationship Management.
Ion Iancu, Mihai Gabroveanu, Mirel Cosulschi & Nicolae Constantinescu. (2007) Implication-Based Support Measures for Fuzzy Association Rules. Implication-Based Support Measures for Fuzzy Association Rules.
Guoqing Chen, Ming Ren, Peng Yan & Xunhua Guo. (2007) Enriching the ER model based on discovered association rules. Information Sciences 177:7, pages 1558-1566.
Crossref
Etienne E. Kerre. 2007. Modeling Decisions for Artificial Intelligence. Modeling Decisions for Artificial Intelligence 1 13 .
Peng Yan & Guoqing Chen. 2006. Fuzzy Applications in Industrial Engineering. Fuzzy Applications in Industrial Engineering 573 587 .
H. Verlinde, M. De Cock & R. Boute. (2005) Fuzzy versus quantitative association rules: a fair data-driven comparison. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 36:3, pages 679-684.
Crossref
M. De Cock, C. Cornelis & E.E. Kerre. (2005) Elicitation of fuzzy association rules from positive and negative examples. Fuzzy Sets and Systems 149:1, pages 73-85.
Crossref
Ya Gao, Jun Ma & Lin Ma. (2004) A new algorithm for mining fuzzy association rules. A new algorithm for mining fuzzy association rules.
Peng Yan, Guoqing Chen, Chris Cornelis, Martine De Cock & Etienne Kerre. 2004. Knowledge-Based Intelligent Information and Engineering Systems. Knowledge-Based Intelligent Information and Engineering Systems 270 276 .

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