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PAKDD
2007
ACM

Two-Phase Algorithms for a Novel Utility-Frequent Mining Model

9 years 17 days ago
Two-Phase Algorithms for a Novel Utility-Frequent Mining Model
When companies seek for the combination of products which can constantly generate high profit, the association rule mining (ARM) or the utility mining will not achieve such task. ARM mines frequent itemsets without knowing the producing profit. On the other hand, the utility mining seeks high profit items but no guarantee the frequency. In this paper, we propose a novel utility-frequent mining model to identify all itemsets that can generate a user specified utility in transactions, in which the percentage of such transactions in database is not less than a minimum support threshold. A utility-frequent itemset indicates that such combination of products can constantly generate high profit. For finding all utility-frequent itemsets, there is no efficient strategy due to the nonexistence of “downward/upward closure property”. In order to tackle such challenge, we propose a bottom-up two-phase algorithm, BU-UFM, for efficiently mining utility-frequent itemsets. We also introduce...
Jieh-Shan Yeh, Yu-Chiang Li, Chin-Chen Chang
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where PAKDD
Authors Jieh-Shan Yeh, Yu-Chiang Li, Chin-Chen Chang
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