학술논문

An advanced network visualization system for financial crime detection
Document Type
Conference
Source
2011 IEEE Pacific Visualization Symposium Visualization Symposium (PacificVis), 2011 IEEE Pacific. :203-210 Mar, 2011
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
General Topics for Engineers
Signal Processing and Analysis
Clustering algorithms
Algorithm design and analysis
Layout
Visualization
Social network services
Terrorism
Companies
Financial Visualization
Crime Detection
Graph Visualization
Graph Clustering
Language
ISSN
2165-8765
2165-8773
Abstract
We present a new system, VISFAN, for the visual analysis of financial activity networks. It supports the analyst with effective tools to discover financial crimes, like money laundering and frauds. If compared with other existing systems and methodologies for the analysis of criminal networks, VISFAN presents the following main novelties: (i) It combines bottom-up and top-down interaction paradigms for the visual exploration of complex networks; (ii) It makes it possible to mix automatic and manual clustering; (iii) It allows the analyst to interactively customize the dimensions of each cluster region and to apply different geometric constraints on the layout. VISFAN also implements several tools for social network analysis other than clustering. For example, it computes several indices to measure the centrality of each actor in the network.