Graph-based Detection
Graph-Based Detection is a detection method that utilizes graph structures to model and analyze relationships among entities, distinguishing itself by identifying suspicious patterns and anomalous behaviors indicative of money laundering through the topological analysis of financial transaction networks.
280
Publications
14.8K
Citations
998
Authors
388
Institutions
Publications per year
2017–2026
184
Parents
280
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
Yingtong Dou, Zhiwei Liu, Li Sun et al. · 2020 · 553 citations · Full text
Caleb C. Noble, Diane J. Cook · 2003 · 471 citations
Shashank Pandit, Duen Horng Chau, Samuel J. Wang et al. · 2007 · 383 citations
Review Graph Based Online Store Review Spammer Detection
Guan Wang, Sihong Xie, Bing Liu et al. · 2011 · 382 citations
1–5 of 280
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388
Carnegie Mellon University
Pittsburgh, United States
15 h-index
39 publications
4.9K citations

Chinese Academy of Sciences
Beijing, China
11 h-index
20 publications
1.2K citations
University of Chinese Academy of Sciences
Beijing, China
8 h-index
28 publications
2.2K citations

Beijing University of Posts and Telecommunications
Beijing, China
8 h-index
23 publications
2.1K citations

Macquarie University
Sydney, Australia
7 h-index
21 publications
1.9K citations

Zhejiang University
Hangzhou, China
7 h-index
10 publications
459 citations
Tsinghua University
Beijing, China
6 h-index
11 publications
896 citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
9 publications
874 citations
1–8 of 388
Repository · 8 publications · 203 citations
8
h-index
6 publications · 302 citations
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TKDE · 6 publications · 305 citations
6
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5 publications · 341 citations
5
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Conference · 5 publications · 250 citations
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