Title :
Lp - Association Rules mining based on rough concept lattice
Author :
Liu, Bao-Xiang ; Xie, Yu-jing ; Xu, Jun ; Zhang, Zhong-peng
Author_Institution :
Coll. of Sci., Hebei Polytech. Univ., Thangshan, China
Abstract :
Rough concept lattice (RCL) is a new concept lattice, which can deal with uncertainty knowledge. It is an effective tool for data analysis and knowledge discovery. But some objects that in upper approximation extent of RCL are so uncertainty that makes the accuracy of association rules reduced. In this case, based on decision context, we construct a L- plumpness concept lattice (Lp - RCL), in whose upper approximation extent objects at least satisfy L attributes in order to improve the efficiency of extraction rules. And we get the algorithm for Lp - association rules.
Keywords :
data analysis; data mining; rough set theory; L- plumpness concept lattice; Lp-association rules mining; data analysis; knowledge discovery; rough concept lattice; uncertainty knowledge; upper approximation extent; Association rules; Cybernetics; Data analysis; Data mining; Educational institutions; Electronic mail; Lattices; Machine learning; Set theory; Uncertainty; Association rules; Lp - set; Rough concept lattice;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212515