Journal of Nuclear Energy Science & Power Generation TechnologyISSN: 2325-9809

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Compact Tree Structures for Mining High Utility Itemsets

High Utility Itemset Mining (HUIM) from large transaction databases has garnered significant attention as it accounts for the revenue of the items purchased in a transaction. While most tree-based algorithms to mine HUIs transform the database to an item-prefix tree, they discard the unpromising items and consume a significant amount of memory. Employing trees that store transaction-level information has proven to enhance the mining process in conjunction with such prefix trees. In this regard, the present work proposes memory-efficient trees namely- Utility Prime Tree (UPT), Prime Cantor Function Tree (PCFT), and String based Utility Prime Tree (SUPT) that encode entire transaction information in a node, unlike the prefix-based trees through a single database scan. Experiments conducted on both the real and synthetic datasets show that these structures consume significantly less memory when compared to the tree structures in the literature.

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