Open Access Open Access  Restricted Access Subscription or Fee Access

A Survey on Improvising Frequent Pattern Mining Methods

Manmay Badheka, Shruti Yagnik, Ompriya Kale, Sagar Gajera


In data mining approaches, association rules mining algorithms are promising for actual applications such as marketing strategies, catalog design. However, the association rules mining is essentially based on a database comprised of Boolean attributes. In order to apply a mining algorithm to further various problems, quantitative attributes should also be appropriately dealt. Fuzzy association rules mining approaches are proposed to overcome such disadvantages based on the fuzzy set concept. The fuzzy association rule mining has a good property in terms of the quantization of numerical attributes of a database compared to generalize Boolean association rule mining. So, the mining results of fuzzy association rules are easy to understand for corresponding human operators.


Association Rule Mining, Fuzzy Association Rule Mining, Membership Function, Certainty Factor

Full Text:



Rathod Arti, Ajaysingh Dhabariya, and Chintan Thacker. "An Approach to Mine Significant Frequent Patterns by Quantity Attribute." Communication Systems and Network Technologies (CSNT), 2014 Fourth International Conference on IEEE, 2014.

Dancheng, Li, et al. "A new approach of self-adaptive discretization to enhance the apriori quantitative association rule mining." Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on IEEE, 2012.

Muyeba, Maybin K., et al. "Understanding Low Back Pain Using Fuzzy Association Rule Mining." Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on IEEE, 2013.

Zheng, Hui, et al. "Optimized fuzzy association rule mining for quantitative data." Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on IEEE, 2014.

Sanjit Kumar Dash, GouravmoyMohanty, Abhishek Mohanty. “Intelligent Air Conditioning System using Fuzzy Logic.” International Journal of Scientific & Engineering Research 2012.

Tarun Kumar Das, Yudhajit Das. ”Design of A Room Temperature And Humidity Controller Using Fuzzy Logic “, American Journal of Engineering Research (AJER), 2013.

Watanabe, Toshihiko, and Ryosuke Fujioka. "Fuzzy association rules mining algorithm based on equivalence redundancy of items." Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on IEEE, 2012.

Matthews, Stephen G., et al. "Temporal fuzzy association rule mining with 2-tuple linguistic representation." Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on IEEE, 2012.

Ghazi, HadiLafzi, and Mohammad SanieeAbadeh. "Mining fuzzy association rules with 2-tuple linguistic terms in stock market data by using genetic algorithm." Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on IEEE, 2012.

T. Watanabe “An Improvement of Fuzzy Association Rules Mining Algorithm Based on Redundancy of Rules,” Proc. of the 2nd International Symposium on Aware Computing, IEEE, 2010.

Han Jiawei, and Micheline Kamber. Data Mining Concepts and Techniques, Southeast Asia Edition. Morgan kaufmann Publisher, 2006. ISBN 1-55860-901-6.

Timothy J. Ross, Fuzzy Logic with Engineering Applications, Wiley, 2010.

S.Rajasekaran and G.A.VijyalakshmiPai, Neural Networks, Fuzzy and Genetic Algorithm, PHI Publication, New Delhi, 2012.

“Fuzzy Logic Membership function”, [online] Available: [November 12, 2014 10:00 am]

“Application of Fuzzy controller on monotone function”, [online] Available: [November 12, 2014 10:15 am]


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.