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Online mining of streaming data is one of the most important issues in data mining. In this paper, we proposed an efficient one-pass algorithm, called MFI-TransSW (Mining Frequent Itemsets over a Transaction-sensitive Sliding Window), to mine the set of all frequent itemsets in data streams with a transaction-sensitive sliding window. An effective bit-sequence representation of items is used in the proposed algorithm to reduce the time and memory needed to slide the windows. The experimentsdoi:10.1109/icsmc.2006.385267 dblp:conf/smc/LiHSL06 fatcat:d3wcu67yk5bfzcwxqtlwehnjei