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Frequent Itemset Mining is playing major role in extracting useful knowledge from data streams that are exhibiting high data flow. Studies in data streams shows that every incoming data is considered as new tuple which is considered as revised tuple in some applications called as tuple evolving data streams. Extracting redundant less knowledge from such kind of application helps in better decision making with new challenges.One of the issue is, due to incoming revised tuple, some of thedoi:10.35940/ijeat.f9107.088619 fatcat:zx3epwpcgfhg7dxjpgelwevsna