Fast algorithm for mining frequent itemsets over data streams
Yu Wang · Computer Engineering and Applications Journal · 2008
Recently,data streams mining has become a research hotspot at home and abroad,while mining frequent itemsets is an important problem in the data streams mining.According to the features of the data streams which is limitless and mobility,an al-gorithm called FIM-SW is proposed to mine the frequent itemsets over the sliding window.The vertical database representation is adopted in the proposed algorithm,each item is represented by bitvector,and the Apriori property is used to get frequent item-sets.The experimental results show that it improves the efficiency for mining observably.