An Efficient Algorithm for Deriving Frequent Itemsets from Lossless Condensed Representation-Reference-Cited by-同舟云学术

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An Efficient Algorithm for Deriving Frequent Itemsets from Lossless Condensed Representation

Published:2019 Issue: Volume: Page:216-229
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Huang JianTao,Lai Yi-Pei,Lo Chieh,Wu Cheng-Wei

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-22999-3_20

Reference22 articles.

1. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proceedings of International Conference on Very Large Data Bases, pp. 487–499 (1994)

2. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);J-F Boulicaut,2000

3. Lecture Notes in Computer Science;T Calders,2002

4. Fournier-Viger, P., Gomariz, A., Gueniche, T., Soltani, A., Wu, C., Tseng, V.S.: SPMF: a Java open-source pattern mining library. J. Mach. Learn. Res. 15, 3569–3573 (2014)

5. Gupta, S., Mamtora, R.: A survey on association rule mining in market basket analysis. Int. J. Inf. Comput. Technol. 4(4), 409–414 (2014)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Fast Algorithm for Deriving Frequent Itemsets;2021 International Conference on Technologies and Applications of Artificial Intelligence (TAAI);2021-11

2. Efficient algorithms for deriving complete frequent itemsets from frequent closed itemsets;Applied Intelligence;2021-04-11

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