Paper Info
Title
Optimized fuzzy association rule mining for quantitative data
Abstract
With the advance of computing and electronic technology, quantitative data, for example, continuous data (i.e., sequences of floating point numbers), become vital and have wide applications, such as for analysis of sensor data streams and financial data streams. However, existing association rule mining generally discover association rules from discrete variables, such as boolean data (`O' and `l') and categorical data (`sunny', `cloudy', `rainy', etc.) but very few deal with quantitative data. In this paper, a novel optimized fuzzy association rule mining (OFARM) method is proposed to mine association rules from quantitative data. The advantages of the proposed algorithm are in three folds: 1) propose a novel method to add the smoothness and flexibility of membership function for fuzzy sets; 2) optimize the fuzzy sets and their partition points with multiple objective functions after categorizing the quantitative data; and 3) design a two-level iteration to filter frequent-item-sets and fuzzy association-rules. The new method is verified by three different data sets, and the results have demonstrated the effectiveness and potentials of the developed scheme.
Year
DOI
Venue
2014
10.1109/FUZZ-IEEE.2014.6891735
FUZZ-IEEE
Keywords
Field
DocType
objective function,optimized fuzzy association rule mining,optimized partition points,fuzzy set theory,quantitative data,sensor data streams,fuzzy sets,boolean data,categorical data,quantitative association rule,frequent-item-sets,data mining,financial data streams,multiple objective functions,two-level iteration,optimization,association rules,linear programming,blood pressure
Data mining,Neuro-fuzzy,Data stream mining,Fuzzy classification,Defuzzification,Computer science,Fuzzy set operations,Fuzzy set,Artificial intelligence,Fuzzy number,Membership function,Machine learning
Conference
ISSN
Citations 
PageRank 
1544-5615
5
0.40
References 
Authors
8
4
Name
Order
Citations
PageRank
Hui Zheng17315.94
Jing He2101.14
Guangyan Huang341942.85
Yanchun Zhang43059284.90