Mining High Transaction-Weighted Utility Itemsets
Guo-Cheng Lan, Tzung‐Pei Hong, Vincent S. M. Tseng
Abstract
Guo-Cheng Lan, Tzung‐Pei Hong, Vincent S. M. Tseng
Abstract
In this paper, we design a new kind of patterns, named high transaction-weighted utility itemsets, which considers not only individual profits and quantities of the items in a transaction, but also the contribution of each transaction in a database. We also propose a two-phased mining algorithm to discover high transaction-weighted utility itemsets. The experimental results on synthetic datasets show the proposed approach has a good performance.
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In this paper, we design a new kind of patterns, named high transaction-weighted utility itemsets, which considers not only individual profits and quantities of the items in a transaction, but also the contribution of each transaction in a database. We also propose a two-phased mining algorithm to discover high transaction-weighted utility itemsets. The experimental results on synthetic datasets show the proposed approach has a good performance.
Key concepts: Database transaction, Computer science, Data mining, Transaction processing, Transaction data, Online transaction processing, Database