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A Fuzzy Close Algorithm for Mining Fuzzy Association Rules [chapter]

Régis Pierrard, Jean-Philippe Poli, Céline Hudelot
2018 Communications in Computer and Information Science  
In this paper, we propose a fuzzy adaptation of the well-known Close algorithm which relies on the closure of itemsets.  ...  Association rules allow to mine large datasets to automatically discover relations between variables.  ...  Conclusion In this paper, we introduced a new fuzzy association rule mining algorithm inspired by the Close algorithm.  ... 
doi:10.1007/978-3-319-91476-3_8 fatcat:t3qvmwhrofaq3d7njxrjqwco3m

Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy

Tzung-Pei Hong, Chun-Hao Chen, Yeong-Chyi Lee, Yu-Lung Wu
2008 IEEE Transactions on Evolutionary Computation  
This paper, thus, proposes a fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions.  ...  A genetic algorithm (GA)-based framework for finding membership functions suitable for mining problems is proposed.  ...  VI CONCLUSION In this paper, we have proposed a GA-based fuzzy data mining algorithm for extracting both association rules and membership functions from quantitative transactions.  ... 
doi:10.1109/tevc.2007.900992 fatcat:apl7s2ebgzfcrddxa6slaadaay

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.  ...  The generated membership functions are subsequently used in a fuzzy temporal association rule mining algorithm.  ...  As a result, many algorithms have been designed to mine fuzzy association rules [2] , [10] , [11] , [22] .  ... 
doi:10.1109/access.2020.3004095 fatcat:jiwbtldgzng3tfkcpebfsyxu54

Post-Analysis Framework for Mining Actionable Patterns Using Clustering and Genetic Algorithms

Chun-Hao Chen, Ji-Syuan He, Tzung-Pei Hong, Subbaiya Rammohan Kannan
2019 IEEE Access  
ACKNOWLEDGMENT This is a modified and expanded version of the paper ''A two-stage multi-objective genetic-fuzzy mining algorithm,'' presented at the 2013 IEEE Symposium Series on Computational Intelligence  ...  One of the best-known mining algorithms for analyzing transactions uses association rules [2] .  ...  patterns include fuzzy generalized association rules and utility fuzzy closed itemsets.  ... 
doi:10.1109/access.2019.2933505 fatcat:24td5h5w3jauflywwyqzyldn3m

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.  ...  The final best minimum supports and membership functions in all the populations are then gathered together to be used for mining fuzzy association rules.  ...  Chan and Au proposed an F-APACS algorithm to mine fuzzy association rules (Chan & Au, 1997) .  ... 
doi:10.1016/j.eswa.2009.01.067 fatcat:iu2ywpoizjhvhghtzxgy34duny

Efficient mining fuzzy association rules from ubiquitous data streams

Amal Moustafa, Badr Abuelnasr, Mohamed Said Abougabal
2015 Alexandria Engineering Journal  
This raises new issues, that need to be considered when developing association rule mining techniques for these data.  ...  In this paper the problem of mining fuzzy association rules from ubiquitous data streams is studied, and a novel technique FFP_USTREAM (Fuzzy Frequent Pattern Ubiquitous Streams) is developed.  ...  Need to extend existing work Close study of Tables 2 and 3 reveals the need to develop a novel technique for mining fuzzy association rules from ubiquitous data streams.This technique should enjoy the  ... 
doi:10.1016/j.aej.2015.03.015 fatcat:ebkj5zx47befrgshwz3aeueqwi

Why Fuzzy Sequential Patterns can Help Data Summarization: An Application to the INPI Trade Mark Database

C. Fiot, A. Laurent, M. Teisseire, B. Laurent
2006 2006 IEEE International Conference on Fuzzy Systems  
Several approaches have been proposed to mine such fuzzy rules, in particular to mine fuzzy association rules.  ...  We show that mining such rules requires to manage a lot of information and we propose algorithms to remain efficient in both memory use and computation time.  ...  Federico Del Razo Lopez for their help in the management and pre-processing of the INPI database.  ... 
doi:10.1109/fuzzy.2006.1681787 dblp:conf/fuzzIEEE/FiotLTL06 fatcat:xux25f6zxjcw5mcwiziugfrd7u

Fuzzy Association Rule Mining

A. Lekha, C. V. Srikrishna, Viji Vinod
2015 Journal of Computer Science  
The paper attempts to propose a fuzzy logic association algorithm to predict the risks involved in identifying diseases like breast cancer. Fuzzy logic algorithm is used to find association rules.  ...  Acknowledgement The researchers thank the principal and management of PESIT, for their continued support. Author's Contributions All authors equally contributed in this work.  ...  There are many known algorithms for mining Boolean association rule such as Apriori, Apriori TID and Apriori Hybrid algorithms for mining association rule (Dorf and Robert, 2010) .  ... 
doi:10.3844/jcssp.2015.71.74 fatcat:pu25qd5mxjbaldgzuf3xruv5v4

ECOGA: Efficient Data Mining Approach for Fuzzy Association Rules

Wanneng Shu, Lixing Ding
2011 Journal of Software  
Experimental results show the number of fuzzy association rules obtained with the proposed method is larger than those obtained by applying other methods. He is currently a professor at the SKLSE.  ...  In this paper an efficient data mining approach, which is based on fuzzy set theory and clonal selection algorithm, is proposed.  ...  In [16] proposed an algorithm that integrates fuzzy set concepts and Apriori mining algorithm to find interesting fuzzy association rules from given transactional data.  ... 
doi:10.4304/jsw.6.1.91-99 fatcat:hffu7dfibzcq5jiidxqnjwvxhq

Fast Mining of Fuzzy Association Rules

Amir Ebrahimzadeh, Reza Sheibani
2012 Journal of clean energy technologies  
Fuzzy association rules described by the natural language are well suited for the thinking of human subject and will help to increase the flexibility for supporting user in making decisions or designing  ...  In this paper, we present an efficient algorithm named fuzzy cluster-based (FCB) along with its parallel version named parallel fuzzy cluster-based (PFCB).  ...  Therefore as the database size becomes larger and larger, a better way is to mine association rules in parallel. A parallel algorithm for mining fuzzy association rules have been proposed in [13] .  ... 
doi:10.7763/ijcte.2012.v4.580 fatcat:7ihumuhbujbgzgbjvebo3sjhva

Rule Extraction For Blood Donators With Fuzzy Sequential Pattern Mining

Fatemeh Zabihi, Mojtaba Ramezan, Mir Mohsen Pedram, Azizollah Memariani
2011 Journal of Mathematics and Computer Science  
In this paper, a fuzzy sequential pattern mining algorithm is applied to mine fuzzy sequential patterns from the Blood  ...  The classical sequential pattern mining algorithms do not allow processing of numerical data and require converting these data into a binary representation, which necessarily leads to a loss of information  ...  In previous study, a number of researchers have exploited fuzzy techniques to mine fuzzy association rules [5] - [8] or sequential patterns from databases [6] , [9] , [10] , such as fuzzy support  ... 
doi:10.22436/jmcs.002.01.05 fatcat:2qaoas5g55aljlaj4nhiwy3h7q

A study on a novel method of mining fuzzy association using fuzzy correlation analysis

Karthikeyan T.
2012 African Journal of Mathematics and Computer Science Research  
To tackle this weakness, a fuzzy correlation measure for fuzzy numbers, is used to augment the fuzzy support-confidence framework for fuzzy association rules.  ...  Mining fuzzy association rules is the job of finding the fuzzy item-sets which frequently occur together in large fuzzy data set, where the presence of one fuzzy item-set in a record does not necessarily  ...  Apriori is a seminal algorithm proposed for mining frequent fuzzy item-sets. The algorithm uses prior knowledge of frequent fuzzy item-set properties.  ... 
doi:10.5897/ajmcsr11.157 fatcat:5jauwyq5ybeqbcgugukqpjholi

Fuzzy Association Rule Mining based Model to Predict Students' Performance

Sushil Kumar Verma, R.S. Thakur, Shailesh Jaloree
2017 International Journal of Electrical and Computer Engineering (IJECE)  
In this paper, student's performance is evaluated using fuzzy association rule mining that describes Prediction of performance of the students at the end of the semester, on the basis of previous database  ...  One approach to get maximum level of quality in higher education system is by discovering knowledge for prediction regarding the internal assessment and end semester examination.  ...  Constructing a Dataset for Mining After having defined the fuzzy sets, a new data set enabling the mining of fuzzy association rules has to be constructed out of the original data.  ... 
doi:10.11591/ijece.v7i4.pp2223-2231 fatcat:rqql2cqxnzarlotilwh3bzx6me

Gain ratio based fuzzy weighted association rule mining classifier for medical diagnostic interface

2014 Sadhana (Bangalore)  
In the past, we have proposed an information gain based fuzzy association rule mining algorithm for extracting both association rules and membership functions of medical data to reduce the rules.  ...  Fuzzy association rule mining is wellperformed better than traditional classifiers but it suffers from the exponential growth of the rules produced.  ...  Apriori algorithm as in AI-Daoud (2010) is a well-known method for rule mining which can be used in fuzzy association rule mining (FARM).  ... 
doi:10.1007/s12046-013-0198-1 fatcat:lbjiozvforfgfe3e4raku2fcra

A new proposal Classification method based on Fuzzy Association Rule Mining for Student Academic Performance Prediction

Giap Cu
2017 VNU Journal of Science Policy and Management Studies  
Theprediction approaching fuzzy association rules (FAR) give advantages in this circumstancebecause it gives the clear data-driven rules for prediction outcome.  ...  Indeed, a modification tree structure of a FP-growth tree is used in fuzzyfrequent itemset mining, when a new requirement rises, the proposed algorithm mines directly inthe tree structure for the best  ...  A new proposal model for Classification based on Fuzzy association rule mining The new model for a student performance prediction system has two stages.  ... 
doi:10.25073/2588-1116/vnupam.4104 fatcat:4cj3d3he6ff6pibsj4x2fqbrre
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