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A Novel Approach for Discovery Quantitative Fuzzy Multi-Level Association Rules Mining Using Genetic Algorithm

Saad M., Abeer A., Sameh G.
2016 International Journal of Advanced Research in Artificial Intelligence (IJARAI)  
Fuzzy association rules mining approaches are intended to defeat such shortcomings based on the fuzzy set theory.  ...  Quantitative multilevel association rules mining is a central field to realize motivating associations among data components with multiple levels abstractions.  ...  Up-to-date, there exist only a few algorithms for quantitative multilevel fuzzy association rule mining (QMLFRL) .  ... 
doi:10.14569/ijarai.2016.050607 fatcat:wxiz2fvqjbgo7iwsksxhhxqfpa

Mining fuzzy coherent rules from quantitative transactions without minimum support threshold

Chun-Hao Chen, Ai-Fang Li, Yeong-Chyi Lee, Tzung-Pei Hong
2012 2012 IEEE International Conference on Fuzzy Systems  
Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from the give quantitative transactions.  ...  In this paper, we thus proposed an algorithm for mining fuzzy coherent rules to overcome those problems with the properties of propositional logic.  ...  Regarding mining approaches for MSFM problems, Lee et al. proposed a mining algorithm that used multiple minimum supports to mine fuzzy association rules [17] .  ... 
doi:10.1109/fuzz-ieee.2012.6251309 dblp:conf/fuzzIEEE/ChenLLH12 fatcat:bnadoodx6na5heh7w4o56vjbou

Cluster-based Membership Function Acquisition Approaches for Mining Fuzzy Temporal Association Rules

Chun-Hao Chen, Hsiang Chou, Tzung-Pei Hong, Yusuke Nojima
2020 IEEE Access  
mechanism for a fuzzy temporal association rule mining algorithm.  ...  Because current approaches have been designed to generate membership functions for mining fuzzy association rules (FARs) in market-basket analysis, in this paper, we propose a membership function tuning  ...  In addition, based on the rule type, we can also know that the existing approaches were proposed for fuzzy association rule or fuzzy temporal association rule mining. III.  ... 
doi:10.1109/access.2020.3004095 fatcat:jiwbtldgzng3tfkcpebfsyxu54

Fuzzy versus quantitative association rules: a fair data-driven comparison

H. Verlinde, M. De Cock, R. Boute
2005 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
A data-driven approach is used to investigate if there is a significant difference between quantitative and fuzzy association rules in large databases.  ...  As opposed to quantitative association rule mining, fuzzy association rule mining is said to prevent the overestimation of boundary cases, as can be shown by small examples.  ...  In [11] , results obtained with quantitative and fuzzy association rule mining are compared for two artificially created data sets.  ... 
doi:10.1109/tsmcb.2005.860134 pmid:16761820 fatcat:rxfrzii5dzbrvivynugxruc254

A fuzzy coherent rule mining algorithm

Chun-Hao Chen, Ai-Fang Li, Yeong-Chyi Lee
2013 Applied Soft Computing  
Many fuzzy data mining approaches have thus been proposed for finding fuzzy association rules with the predefined minimum support from the give quantitative transactions.  ...  Finally, contingency tables are calculated and used for checking those candidate fuzzy coherent rules satisfy the four criteria or not. If yes, it is a fuzzy coherent rule.  ...  Regarding mining approaches for MSFM problems, Lee et al. proposed a mining algorithm that use multiple minimum supports to mine fuzzy association rules [25] .  ... 
doi:10.1016/j.asoc.2012.12.031 fatcat:jgwijhumzbbx5cpxgdxqvolmly

An improved approach to find membership functions and multiple minimum supports in fuzzy data mining

Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng
2009 Expert systems with applications  
In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting minimum supports and membership functions for items from quantitative transactions.  ...  Fuzzy mining approaches have recently been discussed for deriving fuzzy knowledge.  ...  Kuok et al. (1998) proposed a fuzzy mining approach to handle numerical data in databases and derived fuzzy association rules.  ... 
doi:10.1016/j.eswa.2009.01.067 fatcat:iu2ywpoizjhvhghtzxgy34duny

Evolving Temporal Fuzzy Association Rules from Quantitative Data with a Multi-Objective Evolutionary Algorithm [chapter]

Stephen G. Matthews, Mario A. Gongora, Adrian A. Hopgood
2011 Lecture Notes in Computer Science  
A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented.  ...  The novelty of this research lies in exploring the composition of quantitative and temporal fuzzy association rules and the approach of using a hybridisation of a multi-objective evolutionary algorithm  ...  There are two common approaches to mining quantitative association rules. One approach is to tune membership functions and use a deterministic method to induce rules afterwards (e.g., [10] ).  ... 
doi:10.1007/978-3-642-21219-2_26 fatcat:mfq4st2o3vamnn453nigwamhum

Soft Set Approach for Mining Quantitative Association Patterns in Databases

Saakshi Saraf Saakshi Saraf
2013 IOSR Journal of Computer Engineering  
The main aim of the present paper is to develop a soft set approach for mining fuzzy quantitative association patterns in order to address the issues of under prediction and over prediction of these patterns  ...  Association rule mining is an active data mining research area.  ...  There have been several works on quantitative association rule mining such as the application of fuzzy techniques to quantitative association rule mining, the generalized association rule mining for quantitative  ... 
doi:10.9790/0661-1165565 fatcat:edm7tzqqd5a5bm6ts6mokqeeva

A multi-level ant-colony mining algorithm for membership functions

Tzung-Pei Hong, Ya-Fang Tung, Shyue-Liang Wang, Yu-Lung Wu, Min-Thai Wu
2012 Information Sciences  
In the past, we proposed a mining algorithm to find suitable membership functions for fuzzy association rules based on ant colony systems.  ...  The final membership functions in the last level are then outputted to the rule-mining phase to find fuzzy association rules.  ...  [13] thus proposed a mining approach that integrated fuzzy-set concepts with the apriori mining algorithm to find interesting fuzzy itemsets and association rules in quantitative transaction data.  ... 
doi:10.1016/j.ins.2010.12.019 fatcat:jzr5y3scyzg3zhb2n6tlw44wdu

Mining Weighted Association Rules for Fuzzy Quantitative Items [chapter]

Attila Gyenesei
2000 Lecture Notes in Computer Science  
In this paper, we introduce the problem of mining weighted quantitative association rules based on fuzzy approach.  ...  We tackle this problem by using the concept of z-potential frequent subset for each candidate itemset. We give an algorithm for mining such quantitative association rules.  ...  Conclusion We have proposed generalized mining of weighted quantitative association rules based on fuzzy sets for data items.  ... 
doi:10.1007/3-540-45372-5_45 fatcat:v3cgpmwi7fgvlc7gp2dzfho77m

A Survey of Fuzzy Based Association Rule Mining to Find CoOccurrence Relationships

Anubha Sharma, Asst. Prof. Nirupama Tiwari
2014 IOSR Journal of Computer Engineering  
A fuzzy association rule mining (firstly expressed as quantitative association rule mining) has been proposed using fuzzy sets such that quantitative and categorical attributes can be handled.  ...  The techniques are categorized based upon different approaches. This paper provides the major advancement in the approaches for association rule mining using fuzzy algorithms.  ...  Association Rule Mining, FCBAR(Fuzzy Cluster Based Association Rules) The proposed approach dealt with a challenging clustering association rule mining problem of finding interesting association rules.  ... 
doi:10.9790/0661-16158387 fatcat:c2gzdb24y5crzkbh43kpsdilfy

Genetic algorithm based framework for mining fuzzy association rules

M. Kaya, R. Alhajj
2005 Fuzzy sets and systems (Print)  
It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining, simply because characteristics of quantitative  ...  Motivated by this, in this paper we propose an automated method for mining fuzzy association rules.  ...  Gyenesei [8, 9] presented two different methods for mining fuzzy quantitative association rules, namely without normalization and with normalization.  ... 
doi:10.1016/j.fss.2004.09.014 fatcat:b76vzbjx6zgfrlsmwwwd4ir3n4

Fuzzy Inference Algorithm based on Quantitative Association Rules

Ling Wang, Ji-Yuan Dong, Shu-Lin Li
2015 Procedia Computer Science  
In order to develop a data mining system to extract the fuzzy inference rules from the data, in this paper a fuzzy inference algorithm based on quantitative association rule (FI-QAR) is proposed.  ...  the support and confidence level in the Apriori algorithm for quantitative association rules mining.  ...  Conclusion The FI-QAR algorithm is proposed in this paper, which combines TS fuzzy modelling approach and the quantitative association rules mining approach coupled with discretization based on clustering  ... 
doi:10.1016/j.procs.2015.09.166 fatcat:mzvjyl5gqfettn2zti5va7lyr4

Actionable high-coherent-utility fuzzy itemset mining

Chun-Hao Chen, Ai-Fang Li, Yeong-Chyi Lee
2014 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from quantitative transaction databases.  ...  Finally, contingency tables are calculated and used for checking whether a high-utility fuzzy itemset satisfies four criteria. If so, it is a high-coherent-utility fuzzy itemset.  ...  As to different types of fuzzy association rule approaches, Zhao and Yao (2010) presented a general framework for mining fuzzy association rules.  ... 
doi:10.1007/s00500-013-1214-4 fatcat:gsdygmg25rb6tjjcsldj3aq5oe

Multi-objective Genetic Algorithm Based Method for Mining Optimized Fuzzy Association Rules [chapter]

Mehmet Kaya, Reda Alhajj
2004 Lecture Notes in Computer Science  
We propose a multi-objective Genetic Algorithm (GA) based approach for mining fuzzy association rules containing instantiated and uninstantiated attributes.  ...  This paper introduces optimized fuzzy association rules mining.  ...  Summary and Conclusions In this paper, we contributed to the ongoing research on association rules mining by proposing a multi-objective GA based method for mining optimized fuzzy association rules.  ... 
doi:10.1007/978-3-540-28651-6_113 fatcat:moknhacmwjeine4e6uf7bkn3ta
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