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A matrix-based high-utility itemsets mining algorithm over streaming data using sliding windows
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DOI：10.1016/j.datak.2026.102647.png)
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Abstract
En 中文
• First algorithm uses utility-matrix for high-utility mining in data streams.
• A unique prefix-free method needs 2 itemsets to form longer itemsets.
• A merging method without self-nested functions cuts memory waste.
• A new two-stage pruning reduces search space better via matrix.
• Experiments show significant efficiency and memory gains.
Keywords:
Data stream
HUIM
Utility-matrix
Prefix-free extension
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