An Improved and Accurate Measure for Mining Correlated High-Utility Itemsets
This paper introduces an improved version of the Kulczynski measure, a widely used measure for mining correlated high-utility itemsets. This improved measure aims to achieve high accuracy while efficiently extracting itemsets with high utility that are also correlated. Using the Kulczynski measure often results in the generation of imbalanced itemsets in the mining process. In this paper, by considering the imbalance ratio measure in conjunction with the Kulczynski measure, the number of imbalanced itemsets is reduced significantly. To evaluate the performance of the improved measure, the effect of using this measure in comparison with the Kulczynski measure on the standard datasets is considered in the experiments. The results demonstrate the superior accuracy and advantage of using this correlation measure compared to its competitor.
Authors
- Morteza Keshtkaran (ORCID: https://orcid.org/0000-0001-7238-8209)
- Ali Asghar Heidari (ORCID: https://orcid.org/0000-0001-6938-9948)
Institutions
- Shiraz University (IR)
Publication Details
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1109/iccke65377.2024.10874500
- Primary Topic
- Data Mining Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00