High utility pattern mining algorithm over data streams using ext-list.-Reference-Cited by-同舟云学术

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High utility pattern mining algorithm over data streams using ext-list.

Published:2023-08-31 Issue:22 Volume:53 Page:27072-27095
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Han Meng,Li Muhang,Chen Zhiqiang,Wu Hongxin,Zhang Xilong

Funder

National Natural Science Foundation of China

Natural Science Foundation of Ningxia Province

Graduate Innovation Project of North Minzu University

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-023-04925-6.pdf

Reference38 articles.

1. Yun U, Ryang H, Lee G, Fujita H (2017) An efficient algorithm for mining high utility patterns from incremental databases with one database scan. Knowl-Based Syst 124:188–206

2. Dawar S, Goyal V (2015) UP-Hist tree: an efficient data structure for mining high utility patterns from transaction databases. In: Proceedings of the 19th international database engineering & applications symposium, pp 56–61

3. Liu Y, Liao W, Choudhary A (2005) A two-phase algorithm for fast discovery of high utility itemsets. In: Advances in knowledge discovery and data mining: 9th Pacific-Asia Conference, PAKDD 2005, Hanoi, Vietnam, May 18-20, 2005. Proceedings 9. Springer Berlin Heidelberg, pp 689–695

4. Tseng VS, Wu CW, Shie BE et al (2010) UP-Growth: an efficient algorithm for high utility itemset mining. In: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 253–262

5. Duong Q-H, Fournier-Viger P, Ramampiaro H, Nørvåg K, Dam T-L (2018) Efficient high utility itemset mining using buffered utility-lists. Appl Intell 48(7):1859–1877

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