EDBT 2026 Demo / reviewers in the wild / expert
Dongqi Wang 0001
dblp:69/1006-1
· DBLP profile ↗
7ranked-venue papers in the field
0as first author
7since 2021 · last 2025
0000-0002-2572-7658ORCID · conflict
Domains — venue-derived; a paper can count in several
Data Mining & Knowledge Discovery · 3Other / Interdisciplinary · 3Information Retrieval & Web Search · 1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Link Prediction with Reinforced Neighborhood Selection Guided for Heterogeneous Network
Dongming Chen, Shuyue Zhang, Jiangnan Meng, Mingshuo Nie, Dongqi Wang 0001 |
ADMA (4) | 5 |
| 2025 | Link Prediction Based on Enclosing Triadic Subgraphs
Mingshuo Nie, Jianxiang Zhu, Jingyi Chu, Dongming Chen, Dongqi Wang 0001 |
ADMA (3) | 5 |
| 2025 | Multivariate Wind Power Time Series Forecasting with Noise-Filtering Neural ODEs
Dongming Chen, Dongqi Wang 0001 |
CIKM | 3 |
| 2025 | Text Detection in Industrial Design Drawings via Multi-dimensional Feature Fusion and Differentiable Binarization
Mingzhao Xie, Wandong Xue, Dongming Chen, Dongqi Wang 0001 |
ICDAR (4) | 4 |
| 2024 | An Information Cascade Prediction Algorithm Based on Time Series
Dongming Chen, Mingshuo Nie, Zhengping Sun, Huilin Chen 0001, Dongqi Wang 0001 |
MMAsia | 5 |
| 2024 | A Multi-angle Text Recognition Algorithm
Jie Wang 0108, Huilin Chen 0001, Wandong Xue, Dongming Chen, Dongqi Wang 0001 |
MMAsia | 5 |
| 2021 | A survey of community detection methods in multilayer networksabstractAbstract Community detection is one of the most popular researches in a variety of complex systems, ranging from biology to sociology. In recent years, there’s an increasing focus on the rapid development of more complicated networks, namely multilayer networks. Communities in a single-layer network are groups of nodes that are more strongly connected among themselves than the others, while in multilayer networks, a group of well-connected nodes are shared in multiple layers. Most traditional algorithms can rarely perform well on a multilayer network without modifications. Thus, in this paper, we offer overall comparisons of existing works and analyze several representative algorithms, providing a comprehensive understanding of community detection methods in multilayer networks. The comparison results indicate that the promoting of algorithm efficiency and the extending for general multilayer networks are also expected in the forthcoming studies. Xinyu Huang 0002, Dongming Chen, Tao Ren 0002, Dongqi Wang 0001 |
Data Min. Knowl. Discov. | 4 |