An Algorithm of Top-k High Utility Itemsets Mining over Data Stream

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Provided by: Academy Publisher
Topic: Data Management
Format: PDF
Existing top-k High Utility Itemset (HUI) mining algorithms generate candidate itemsets in the mining process; their time & space performance might be severely affected when the dataset is large or contains many long transactions; and when applied to data streams, the performance of corresponding mining algorithm is especially crucial. To address this issue, propose a sliding window based top-k HUIs mining algorithm TOPK-SW; it first stores each batch data of current window as well as the items' utility information to a tree called HUI-tree, which ensures effective retrieval of utility values without re-scan the dataset, so as to efficiently improve the mining performance.
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