DocumentCode :
3521509
Title :
Research on Mining Frequent Itemsets Based on Bitwise AND Algorithm
Author :
Guo Xiaoli ; Feng Li ; Guo Ping
Author_Institution :
Sch. of Inf. Eng., Northeast Dianli Univ., Jilin, China
fYear :
2011
fDate :
28-29 May 2011
Firstpage :
1
Lastpage :
4
Abstract :
According to the characteristics of the data flow, the article puts forward a new frequent itemsets mining algorithm based on bitwise and computation. Algorithm uses basic window for unit, and update sliding window in memory using arrays structure maintenance item of frequent information, finally by the frequent items between the bitwise and operations to get all the frequent itemsets. Algorithm in each basic window goes into the sliding window after dynamically update arrays, analysis and experiment shows that the algorithm has better performance.
Keywords :
data flow computing; data mining; user interfaces; array structure maintenance; bitwise AND algorithm; data flow characteristics; frequent itemset mining; memory sliding window; Algorithm design and analysis; Arrays; Data mining; Heuristic algorithms; Itemsets; Memory management; Substations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems and Applications (ISA), 2011 3rd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9855-0
Electronic_ISBN :
978-1-4244-9857-4
Type :
conf
DOI :
10.1109/ISA.2011.5873398
Filename :
5873398
Link To Document :
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