IHUMN: an improved high-utility itemsets mining algorithm with negative utility items-Reference-Cited by-同舟云学术

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IHUMN: an improved high-utility itemsets mining algorithm with negative utility items

Published:2022-12-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence
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Author:

Wang Huijiao¹^ORCID,Wei Jinghai¹^ORCID,Wang Xin¹^ORCID,Li Xing¹^ORCID,Jiang Hua¹^ORCID

Affiliation:

1. School of Computer Science and Information Security, Guilin University of Electronic Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3579654.3579766

Reference23 articles.

1. High-Utility Pattern Mining

2. A survey on association rules mining using heuristics

3. A regression-based algorithm for frequent itemsets mining

4. Valiullin T , Huang ZX , Wei CH , Yin JF , Wu DM , Egorova I. A new approximate method for mining frequent itemsets from big data. Comput Sci Inf Syst. 202 1;18(3): 641 – 656 . Valiullin T, Huang ZX, Wei CH, Yin JF, Wu DM, Egorova I. A new approximate method for mining frequent itemsets from big data. Comput Sci Inf Syst. 2021;18(3):641–656.

5. Agrawal R , Srikant R. Fast Algorithms for Mining Association Rules in Large Databases. Proceedings of the 20th International Conference on Very Large Data Bases; 1994 Sep; Santiago de Chile. Agrawal R, Srikant R. Fast Algorithms for Mining Association Rules in Large Databases. Proceedings of the 20th International Conference on Very Large Data Bases; 1994 Sep; Santiago de Chile.

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