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In recent years, the mining research over data stream has been prominent as they can be applied in many alternative areas in the real worlds. In , a framework for mining frequent itemsets over a data stream is proposed by the use of weighted slide window model. Two algorithms of single pass (WSW) and the WSW-Imp (improving one) using weighted sliding model were proposed in there to solve the data stream problems. The disadvantage of these algorithms is that they have to seek all data streamdoi:10.5815/ijisa.2015.12.02 fatcat:o7mu6rxfondglkueq7rtquatai