Closed Frequent Itemsets mining over Data streams for Visualizing Network Traffic

The main objective of Network monitoring is to understand the active events that happen frequently and can influence or ruin the network. In this paper, we have introduced an efficient method of Closed Frequent item set mining over data streams for visualizing these events. The proposed MFCI-SWI ( Mining Frequent Closed Item sets using Sliding Window with Intersection method) algorithm processes the data stream for mining only when user requires. Otherwise simply slides the window and receive the new transactions. Experimental evaluations on real datasets show that our proposed method outperforms recently proposed TMoment algorithm.