Improved Genetic Algorithm for High-Utility Itemset Mining

High-utility itemset mining (HUIM) is an important research topic in the data mining field. Typically, traditional HUIM algorithms must handle the exponential problem of huge search space when the database size or number of distinct items is very large. As an alternative and effective approach, evol...

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Bibliographic Details
Published in:IEEE Access
Main Authors: Qiang Zhang, Wei Fang, Jun Sun, Quan Wang
Format: Article
Language:English
Published: IEEE 2019-01-01
Subjects:
Data mining
high-utility itemset mining
genetic algorithm
neighborhood exploration
diversity maintenance
Online Access:https://ieeexplore.ieee.org/document/8926353/

Internet

https://ieeexplore.ieee.org/document/8926353/

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