Title :
Research of an association rule mining algorithm based on FP tree
Author :
Juan, Li ; De-ting, Ming
Author_Institution :
Comput. & Inf. Eng. Inst., Jiangxi Agric. Univ., Nanchang, China
Abstract :
Based on analyzing an association rule mining algorithm called FP tree, a new association rule mining algorithm called QFP was presented. Through scanning the database only once, the QFP algorithm can convert a transaction database into a QFP tree after data preprocessing, and then do the association rule mining of the tree. The QFP algorithm is more integrity than the FP_growth algorithm, and retain the complete information for mining frequent patterns; it will not destroy the long pattern of any transaction, and significantly reduce the non-relevant information. Experiments show that the QFP algorithm is more efficient if the aspect of time than the FP_growth algorithm.
Keywords :
data mining; transaction processing; tree searching; FP tree; QFP algorithm; association rule mining; data preprocessing; frequent pattern; transaction database; Databases; Electronics packaging; Random access memory; Association rule mining; FP_growth algorithm; Frequent Pattern(FP); QFP algorithm;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658443