Title :
Based on Frequent Itemset for Maximal Frequent Itesets
Author :
Chen, Donghui ; Liu, Zhijing
Author_Institution :
Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´´an, China
Abstract :
This paper proposes a maximal frequent itemsets mining algorithm BFI-MFI (Based on Frequent Itemset for maximal frequent itemsets). A maximal frequent itemset in frequent itemsets can be confirmed through detecting whether exiting their superset. This algorithm provides a new method, which improve the mining efficiency.
Keywords :
data mining; BFI-MFI algorithm; association rule; data mining; maximal frequent itemset; mining algorithm; superset; Algorithm design and analysis; Computers; Data mining; Educational institutions; Itemsets; Research and development; Software algorithms; association rule; data mining; frequent itemset; maximal frequent itemset;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.1424
