DocumentCode :
3473216
Title :
Fast Updating Maximal Frequent Itemsets Based on Full Merged Sorted FP-Tree
Author :
Guo Yunkai ; Yang Junrui ; Huang Yulei
Author_Institution :
Dept. of Comput. Sci., Xi´an Univ. of Sci. & Technol., Xian
fYear :
2008
fDate :
12-14 Oct. 2008
Firstpage :
1
Lastpage :
4
Abstract :
Because of the low efficiency of Maximal Frequent Itemsets(MFI) updating methods, the MFI´s updating methods were analyzed. A new algorithm UAMFI based on Full Merged Sorted FP-Tree (FMSFP-Tree) was proposed. By merging the Sorted FP-Tree and then obtaining the FMSFP-Tree, UAMFI uses the depth-first method to find and update MFI. Finally, the algorithm was tested on the mushroom and T15I4D100K database, and UAMFI´s performances were compared with Mafia. The experimental results indicate that UAMFI is an efficient algorithm for updating Maximal Frequent Itemsets.
Keywords :
data mining; merging; sorting; tree data structures; tree searching; data mining; depth-first method; full merged sorted FP-tree; maximal frequent itemset updating method; Association rules; Clustering algorithms; Computer science; Data mining; Data structures; Frequency; Itemsets; Merging; Testing; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
Type :
conf
DOI :
10.1109/WiCom.2008.2662
Filename :
4680851
Link To Document :
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