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.

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Publication Details

Published
2024-11-19
DOI
https://doi.org/10.1109/iccke65377.2024.10874500
Primary Topic
Data Mining Algorithms and Applications
Type
article
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article

An Improved and Accurate Measure for Mining Correlated High-Utility Itemsets

Morteza Keshtkaran, Ali Asghar Heidari
Data Mining Algorithms and Applications
article

An Improved and Accurate Measure for Mining Correlated High-Utility Itemsets

Morteza Keshtkaran, Ali Asghar Heidari
article en

Abstract

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.

Shiraz University (IR)
Openalex Percentile: Top 56%
Data Mining Algorithms and Applications
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