most citedA Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

cs.LG2025

Graph Neural Network-Driven Hierarchical Mining for Complex Imbalanced Data

Yijiashun Qi, Quanchao Lu, Shiyu Dou +3

This study presents a hierarchical mining framework for high-dimensional imbalanced data, leveraging a depth graph model to address the inherent performance limitations of conventi…

cs.DB2024★ 2 cited

A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets

Xuan Li, Tingyi Ruan, Yankaiqi Li +2

This paper proposes a frequent itemset mining algorithm based on the Boolean matrix method, aiming to solve the storage and computational bottlenecks of traditional frequent patter…