High Utility Itemset Mining: A Thorough Examination of Data Mining  Methods, Algorithms, and Uses

Dharmbir, Ram Kinkar Pandey, Rajiv Kumar

High Utility Itemset Mining: A Thorough Examination of Data Mining Methods, Algorithms, and Uses

Authors

Dharmbir, Ram Kinkar Pandey, Rajiv Kumar

Keywords:

Abstract

The High Utility Itemset Mining (HUIM) is an important revolution in the data mining world as itprovides organizations and researchers with the option of mining patterns that are not onlycommon but also profitable and relevant in the context. A distinction between the HUIM andtraditional association

References

Abhinav, Krishnamurthy, N., & Jain, R. (2018). Wear Studies of Al2O3-ZrO2∙5CaO Composite Coatings for Tribological Applications. International Journal of Engineering & Technology, 7(3.4), 73. https://doi.org/10.14419/ijet.v7i3.4.16750

Agrawal, R., & Srikant, R. (1994). Fast algorithms for mining association rules. Proceedings of the 20th International Conference on Very Large Data Bases (VLDB), 487–499

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Published

2024-08-20

How to Cite

Dharmbir, Ram Kinkar Pandey, Rajiv Kumar. (2024). High Utility Itemset Mining: A Thorough Examination of Data Mining Methods, Algorithms, and Uses. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 6156–6171. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3644