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cs.DB2026

Efficient Mining of Low-Utility Sequential Patterns

Jian Zhu, Zhidong Lin, Wensheng Gan +1

Discovering valuable insights from rich data is a crucial task for exploratory data analysis. Sequential pattern mining (SPM) has found widespread applications across various domai…

cs.DB2026

High-utility Sequential Rule Mining Utilizing Segmentation Guided by Confidence

Chunkai Zhang, Jiarui Deng, Maohua Lyu +2

Within the domain of data mining, one critical objective is the discovery of sequential rules with high utility. The goal is to discover sequential rules that exhibit both high uti…

cs.DB2026

Discovering High-utility Sequential Rules with Increasing Utility Ratio

Zhenqiang Ye, Wensheng Gan, Gengsen Huang +2

Utility-driven mining is an essential task in data science, as it can provide deeper insight into the real world. High-utility sequential rule mining (HUSRM) aims at discovering se…

cs.DB2025

Utility-based Privacy Preserving Data Mining

Qingfeng Zhou, Wensheng Gan, Zhenlian Qi +1

With the advent of big data, periodic pattern mining has demonstrated significant value in real-world applications, including smart home systems, healthcare systems, and the medica…

cs.DB2025

Targeted Mining of Time-Interval Related Patterns

Shuang Liang, Lili Chen, Wensheng Gan +2

Compared to frequent pattern mining, sequential pattern mining emphasizes the temporal aspect and finds broad applications across various fields. However, numerous studies treat te…

cs.DB2024

Targeted Mining Precise-positioning Episode Rules

Jian Zhu, Xiaoye Chen, Wensheng Gan +2

The era characterized by an exponential increase in data has led to the widespread adoption of data intelligence as a crucial task. Within the field of data mining, frequent episod…