Title :
Effective Mining of Fuzzy Quantitative Weighted Association Rules
Author :
Li Cheng-jun ; Yang Tian-qi
Author_Institution :
Dept. of Comput., Univ. of Jinan, Guangzhou, China
Abstract :
This paper presents a new method of mining weighted association rules, which can hold the “weighted downward closed property” by using an improved model of weighted support measurements in the weighted setting. Compared to some generalized weighted association rules mining, it proves that the method can quickly and efficiently mine important association rules.
Keywords :
authorisation; data mining; fuzzy set theory; fuzzy quantitative weighted association rule mining; generalized weighted association rule mining; weighted downward closed property; weighted support measurement model; Algorithm design and analysis; Association rules; Fuzzy sets; Itemsets; quantitative itemsets; weighted association rules; weighted support;
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
DOI :
10.1109/ICEE.2010.360
