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Jinyu Duan

dblp:398/4732 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2026
0009-0004-8927-6907ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Graph algorithms and graph theory · 73% Algorithms and data structures · 27%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures › dynamic algorithms
dynamic graph algorithms
1.012026
Network Dismantling via Reverse Dismantling: Static and Dynamic Algorithms · WWW 2026
Graph algorithms and graph theory › network analysis
network dismantling
1.012026
Network Dismantling via Reverse Dismantling: Static and Dynamic Algorithms · WWW 2026
Graph algorithms and graph theory
cohesive subgraph mining
0.912025
The k-Trine Cohesive Subgraph and Its Efficient Algorithms · KDD (1) 2025
Graph algorithms and graph theory › dense subgraph discovery
k-truss
0.912025
The k-Trine Cohesive Subgraph and Its Efficient Algorithms · KDD (1) 2025

Methods — techniques the papers use, named apart from their topics

tree-like index · 1.0reverse dismantling heuristic · 1.0
YearPublicationVenuePosition
2026 Network Dismantling via Reverse Dismantling: Static and Dynamic Algorithms
abstract
For complex networks such as the Web, the Network Dismantling (ND) problem, which asks for the minimum-cost removal of nodes that destroys the giant connected component in the network, is significant in system robustness and misinformation containment. In this paper, we propose a heuristic algorithm, IG+, which is based on reverse dismantling and incorporates novel optimizations. Besides, we design two dynamic algorithms, CCRT-ins and CCRT-rem, employing tree-like indexes to update dismantling results efficiently. Experiments show that our methods outperform state-of-the-art approaches in both effectiveness and efficiency, and can dismantle 10-million-scale networks at arbitrary granularity in a few minutes.
Jinyu Duan, Sijin Wang, Fan Zhang 0036, Xiang Zhao 0002, Wenjie Zhang 0001, Zhihong Tian 0001
WWW1
2025 The k-Trine Cohesive Subgraph and Its Efficient Algorithms
Jinyu Duan, Haicheng Guo, Fan Zhang 0036, Kai Wang 0037, Zhengping Qian, Zhihong Tian 0001
KDD (1)1