13 citations · 18 across the 9 of their papers we have counts for
4 papers · 1 filter
Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs
Ahmad Naser Eddin, Jacopo Bono, David Aparício +4
Money laundering is a global problem that concerns legitimizing proceeds from serious felonies (1.7-4 trillion euros annually) such as drug dealing, human trafficking, or corruptio…
GUDIE: a flexible, user-defined method to extract subgraphs of interest from large graphs
Maria Inês Silva, David Aparício, Beatriz Malveiro +2
Large, dense, small-world networks often emerge from social phenomena, including financial networks, social media, or epidemiology. As networks grow in importance, it is often nece…
Finding NeMo: Fishing in banking networks using network motifs
Xavier Fontes, David Aparício, Maria Inês Silva +3
Banking fraud causes billion-dollar losses for banks worldwide. In fraud detection, graphs help understand complex transaction patterns and discovering new fraud schemes. This work…
GuiltyWalker: Distance to illicit nodes in the Bitcoin network
Catarina Oliveira, João Torres, Maria Inês Silva +3
Money laundering is a global phenomenon with wide-reaching social and economic consequences. Cryptocurrencies are particularly susceptible due to the lack of control by authorities…