DocumentCode
2492104
Title
Fast mining maximal frequent itemsets based on Sorted FP-tree
Author
Yang, Junrui ; Guo, Yunkai ; Liu, Nanyan
Author_Institution
Dept. of Comput. Sci., Xian Univ. of Sci. & Technol., Xian
fYear
2008
fDate
25-27 June 2008
Firstpage
5391
Lastpage
5395
Abstract
In order to improve the efficiency of mining maximal frequent itemsets, a new algorithm SFP-Miner based on Sorted FP-Tree(SFP-Tree) was proposed. The algorithm scanned the database twice and generated the SFP-Tree first, then mined maximal frequent itemsets by depth-first method and directly in SFP-Tree by merging sub-trees, finally obtained the maximal frequent itemsets. The experimental results indicate that SFP-Miner is an efficient algorithm. It has superior to the algorithm Mafia in performance.
Keywords
data mining; tree searching; Mafia algorithm; SFP-Miner algorithm; Sorted FP-tree; database; depth-first method; maximal frequent itemsets mining; Association rules; Automation; Computer science; Data mining; Intelligent control; Itemsets; Merging; Transaction databases; SFP-Tree; association rule; data mining; maximal frequent itemsets;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4593808
Filename
4593808
Link To Document