MEMU: More Efficient Algorithm to Mine High Average-Utility Patterns With Multiple Minimum Average-Utility Thresholds

MEMU: More Efficient Algorithm to Mine High Average-Utility Patterns With Multiple Minimum Average-Utility Thresholds

High average-utility itemsets mining (HAUIM) is an emerging topic in data mining. Compared to traditional high utility itemset mining, HAUIM more fairly measures the utility of itemsets by considering their lengths (number of items). Many previous studies have presented algorithms to efficiently min...

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Bibliographic Details
Main Authors: Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Data mining
high average-utility itemsets
list structure
multiple thresholds
Online Access:https://ieeexplore.ieee.org/document/8279384/

Internet

https://ieeexplore.ieee.org/document/8279384/

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