An Algorithm of Frequent Item Sets Mining Based on Transformation of the Frequent Item Linked
Haiyan Zhou · Journal of Chinese Computer Systems · 2008
The generation of the frequent item linked list set is a main problem in the association rules data mining.The recent researches have being to explore the propriety data structures so as to support the minimal scan of the transactions database reduce the immense I/O consume,and got more efficiency.In this paper,an algorithm of association rules data mining named FILLT is suggested,It only need two times of scanning the transactions database the algorithm use the strategy of dividing and ruling to proceed the association rules data mining by dividing and translating the frequent item linked list At the end of the paper the efficiency of the algorithm analyzed theoretically and tested experimentally.