DocumentCode
468353
Title
A Two-Way Hybrid Algorithm for Maximal Frequent Itemsets Mining
Author
Chen, Fu-zan ; Li, Min-qiang
Author_Institution
Tianjin Univ., Tianjin
Volume
3
fYear
2007
fDate
24-27 Aug. 2007
Firstpage
499
Lastpage
503
Abstract
A new two-way-hybrid algorithm for mining maximal frequent itemsets is proposed. A flexible two-way-hybrid search method is given. The two-way-hybrid search begins the mining procedure in both the top-down and bottom-up directions at the same time. Moreover, information gathered in the bottom-up can be used to prune the search space in the other top-down direction. Some efficient decomposition and pruning strategies are implied in this method, which can reduce the original search space rapidly in the iterations. Experimental and analytical results are presented in the end.
Keywords
data mining; set theory; tree data structures; tree searching; bottom-up search; maximal frequent itemset mining; pruning strategy; top-down search; tree data structure; Data mining; Frequency shift keying; Fuzzy systems; Itemsets; Optimization methods; Search methods; Transaction databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2874-8
Type
conf
DOI
10.1109/FSKD.2007.130
Filename
4406288
Link To Document