DocumentCode :
1819924
Title :
An efficient algorithm for incremental mining of association rules
Author :
Chang, Chin-Chen ; Li, Yu-Chiang ; Lee, Jung-San
Author_Institution :
Dept. of Inf. Eng. & Comput. Sci., Feng Chia Univ., Taichung, Taiwan
fYear :
2005
fDate :
3-4 April 2005
Firstpage :
3
Lastpage :
10
Abstract :
Incremental algorithms can manipulate the results of earlier mining to derive the final mining output in various businesses. This study proposes a new algorithm, called the New Fast UPdate algorithm (NFUP) for efficiently incrementally mining association rules from a large transaction database. NFUP is a backward method that only requires scanning incremental database. Rather than rescanning the original database for some new generated frequent itemsets in the incremental database, we accumulate the occurrence counts of newly generated frequent itemsets and delete infrequent itemsets obviously. Thus, NFUP need not rescan the original database and to discover newly generated frequent itemsets. NFUP has good scalability in our simulation.
Keywords :
data mining; transaction processing; very large databases; New Fast UPdate algorithm; association rules; frequent itemsets; incremental database; incremental mining; large transaction database; Algorithm design and analysis; Association rules; Computer science; Data mining; Data warehouses; Information retrieval; Information science; Itemsets; Scalability; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Research Issues in Data Engineering: Stream Data Mining and Applications, 2005. RIDE-SDMA 2005. 15th International Workshop on
ISSN :
1097-8585
Print_ISBN :
0-7695-2390-0
Type :
conf
DOI :
10.1109/RIDE.2005.6
Filename :
1498225
Link To Document :
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