collaborators

5 papers

cs.DB2026

Mining Negative Sequential Patterns to Improve Viral Genomic Feature Representation and Classification

Wenxi Zhu, Wensheng Gan, Zhenlian Qi

Viruses represent the most abundant biological entities on Earth and play a pivotal role in microbial ecosystems, yet, as prominent human pathogens, they are closely linked to huma…

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.LG2026

Graph-Based Fraud Detection with Dual-Path Graph Filtering

Wei He, Wensheng Gan, Philip S. Yu

Fraud detection on graph data can be viewed as a demanding task that requires distinguishing between different types of nodes. Because graph neural networks (GNNs) are naturally su…

cs.DB2025

Targeted Sequential Pattern Mining with High Average Utility

Kai Cao, Yucong Duan, Wensheng Gan

Incorporating utility into targeted pattern mining can address the practical limitations of traditional frequency-based approaches. However, utility-based methods often suffer from…

cs.DB2025

Dual Pruning and Sorting-Free Overestimation for Average-Utility Sequential Pattern Mining

Kai Cao, Yucong Duan, Wensheng Gan

In a quantitative sequential database, numerous efficient algorithms have been developed for high-utility sequential pattern mining (HUSPM). HUSPM establishes a relationship betwee…