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Mining Algorithm for Maximum Frequent Itemsets Based on Bit String Array

YANG Xu-dong, SONG Yu-qing, ZHU Yu-quan (School of Computer Science and Communications Eng., Jiangsu University, Zhenjiang Jiangsu 212013, China)  
Based on the association rule mining algorithm with bit string array,a fast algorithm for mining maximum frequent itemsets with bit string array(BSA-MFIA) is proposed.It scans transaction database D twice and creates the bit string array constructed by “0” and “1”.The bit string array is very suitable for compressing,coding and storing.It may save the storage of the memory efficiently.Then,the maximum frequent itemsets can be mined by using the simple bit operations.As a result,the algorithm not only facilitates the implementation,but also improves the mining efficiency.
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