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- W2167004500 abstract "In this paper, we considers the problem of mining with weighted support over a data stream sliding window using limited memory space. The continuous characteristic of streaming data necessitates the use of algorithms that require only one scan over the stream for knowledge discovery. This paper focuses on research issues concerning mining frequent itemsets in data streams and we suggests an efficient algorithm WSFI-Mine to mine all frequent itemsets. Our experiment show that our algorithm not only achieved effectively consumes less memory, but also runs significantly faster than THUI-mine." @default.
- W2167004500 created "2016-06-24" @default.
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- W2167004500 date "2009-01-01" @default.
- W2167004500 modified "2023-09-24" @default.
- W2167004500 title "Mining Weighted Frequent Itemsets Using Window Sliding over Data Streams" @default.
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- W2167004500 doi "https://doi.org/10.1109/iccit.2009.20" @default.
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