Title :
An Efficient Frequent Itemset Mining Algorithm
Author :
Luo, Ke ; Zhang, Xue-mao
Author_Institution :
Changsha Univ. of Sci. & Technol., Changsha
Abstract :
Frequent itemset mining is a critical step in association rule mining and plays an important role in many data mining tasks including strong rules, correlations and sequential rules. Diffset is an efficient frequent itemset mining algorithm which uses vertical database layout. An efficient hybrid algorithm DiffsetHybrid is brought out. The tests indicate that the new algorithm shows good performance with both sparse datasets and dense datasets.
Keywords :
data mining; database management systems; Diffset frequent itemset mining algorithm; DiffsetHybrid algorithm; association rule mining; data mining tasks; sequential rules; strong rules; vertical database layout; Association rules; Cybernetics; Data mining; Electronic mail; Itemsets; Machine learning; Machine learning algorithms; Telecommunications; Testing; Transaction databases; Diffset; DiffsetHybrid; Frequent itemset mining;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370245
