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20232025
most citedGenerative-Contrastive Heterogeneous Graph Neural Network

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.DB2025

NSPG-Miner: Mining Repetitive Negative Sequential Patterns

Yan Li, Zhulin Wang, Jing Liu +4

Sequential pattern mining (SPM) with gap constraints (or repetitive SPM or tandem repeat discovery in bioinformatics) can find frequent repetitive subsequences satisfying gap const…

cs.DB2024

Order-preserving pattern mining with forgetting mechanism

Yan Li, Chenyu Ma, Rong Gao +4

Order-preserving pattern (OPP) mining is a type of sequential pattern mining method in which a group of ranks of time series is used to represent an OPP. This approach can discover…

cs.LG2024

Transformer-based Graph Neural Networks for Battery Range Prediction in AIoT Battery-Swap Services

Zhao Li, Yang Liu, Chuan Zhou +4

The concept of the sharing economy has gained broad recognition, and within this context, Sharing E-Bike Battery (SEB) have emerged as a focal point of societal interest. Despite t…

cs.LG2024

: Synergistic Boosting of Structure and Representation for Deep Graph Clustering

Shifei Ding, Benyu Wu, Xiao Xu +2

Employing graph neural networks (GNNs) for graph clustering has shown promising results in deep graph clustering. However, existing methods disregard the reciprocal relationship be…

cs.LG2024★ 1 cited

Generative-Contrastive Heterogeneous Graph Neural Network

Yu Wang, Lei Sang, Yi Zhang +2

Heterogeneous Graphs (HGs) effectively model complex relationships in the real world through multi-type nodes and edges. In recent years, inspired by self-supervised learning (SSL)…

cs.DB2023

Repetitive nonoverlapping sequential pattern mining

Meng Geng, Youxi Wu, Yan Li +4

Sequential pattern mining (SPM) is an important branch of knowledge discovery that aims to mine frequent sub-sequences (patterns) in a sequential database. Various SPM methods have…

cs.DB2023

Top-k contrast order-preserving pattern mining

Youxi Wu, Yufei Meng, Yan Li +4

Recently, order-preserving pattern (OPP) mining, a new sequential pattern mining method, has been proposed to mine frequent relative orders in a time series. Although frequent rela…