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- W2124374417 abstract "Mining closed frequent itemsets in the sliding window is one of important topics of data streams mining. In this paper, we propose a novel algorithm, FPCFI-DS, which mines closed frequent itemsets in the sliding window of data streams efficiently, and maintains the precise closed frequent itemsets in the current window at any time. The algorithm uses a single-pass lexicographical-order FP-Tree-based algorithm with mixed item ordering policy to mine the closed frequent itemsets in the first window, and introduces a novel updating approach to process the sliding of window. The experimental results show that FPCFI-DS performs better than the state-of-the-art algorithm Moment in terms of both the time and space efficiencies, especially for dense dataset or low minimum support." @default.
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- W2124374417 date "2008-07-01" @default.
- W2124374417 modified "2023-09-27" @default.
- W2124374417 title "An Efficient Algorithm for Mining Closed Frequent Itemsets in Data Streams" @default.
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- W2124374417 doi "https://doi.org/10.1109/cit.2008.workshops.52" @default.
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