Research on Algorithm for Mining Frequent Closed Itemsets over Data Stream

This paper presents a new efficient algorithm for mining frequent closed item sets in sliding windows over data streams. It divides the sliding window into several basic windows. The basic window of a sliding window was served as an updating unit in this algorithm. And all potential frequent closed item sets of every basic window were mined by comparing the support and relationship of inclusion between item sets. Those itemsets were stored in a new data structure. And the frequent closed itemsets in a sliding window could be rapidly found based on the new data structure. The experimental result shows the feasibility and effectiveness of the algorithm.