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Finding high-importance patterns in data is an emerging data mining task known as High-utility itemset mining (HUIM). Given a minimum utility threshold, a HUIM algorithm extracts all the high-utility itemsets (HUIs) whose utility values are not less
Externí odkaz:
http://arxiv.org/abs/2303.14510
For applied intelligence, utility-driven pattern discovery algorithms can identify insightful and useful patterns in databases. However, in these techniques for pattern discovery, the number of patterns can be huge, and the user is often only interes
Externí odkaz:
http://arxiv.org/abs/2206.06157
Traditional high-utility itemset mining (HUIM) aims to determine all high-utility itemsets (HUIs) that satisfy the minimum utility threshold (\textit{minUtil}) in transaction databases. However, in most applications, not all HUIs are interesting beca
Externí odkaz:
http://arxiv.org/abs/2111.00309
Publikováno v:
In Engineering Applications of Artificial Intelligence November 2023 126 Part D
Akademický článek
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Publikováno v:
Journal of Combinatorial Optimization; Oct2022, Vol. 44 Issue 3, p1637-1658, 22p
The conference proceeding LNCS 11346 constitutes the refereed proceedings of the 12th International Conference on Combinatorial Optimization and Applications, COCOA 2018, held in Atlanta, GA, USA, in December 2018. The 50 full papers presented were