An overview of high utility itemsets mining methods based on intelligent optimization algorithms-Reference-Cited by-同舟云学术

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An overview of high utility itemsets mining methods based on intelligent optimization algorithms

Published:2022-09-03 Issue:11 Volume:64 Page:2945-2984
ISSN:0219-1377
Container-title:Knowledge and Information Systems
language:en
Short-container-title:Knowl Inf Syst

Author:

Han Meng,Gao Zhihui,Li Ang,Liu Shujuan,Mu Dongliang

Funder

National Natural Science Foundation of China

Natural Science Foundation of Ningxia

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s10115-022-01741-1.pdf

Reference65 articles.

1. Nouioua M, Fournier-Viger P, Wu CW (2021) FHUQI-miner: fast high utility quantitative itemset mining. Appl Intell 51(10):6785–6809

2. Ahmed U, Srivastava G, Lin JCW (2021) A federated learning approach to frequent itemset mining in cyber-physical systems. J Netw Syst Manage 29(4):1–17

3. Hidouri A, Jabbour S, Raddaoui B (2021) Mining closed high utility itemsets based on propositional satisfiability. Data Knowl Eng 136:101927

4. Nouioua M, Fournier-Viger P, Gan W (2022) TKQ: top-K quantitative high utility itemset mining[C]. International conference on advanced data mining and applications. Springer, Cham, pp 16–28

5. Sohrabi MK (2020) An efficient projection-based method for high utility itemset mining using a novel pruning approach on the utility matrix. Knowl Inf Syst 62(11):4141–4167

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