NDLI: An advanced network visualization system for financial crime detection

Content Provider	IEEE Xplore Digital Library
Author	Didimo, W. Liotta, G. Montecchiani, F. Palladino, P.
Copyright Year	2011
Description	Author affiliation: University of Perugia, Italy (Didimo, W.; Liotta, G.; Montecchiani, F.; Palladino, P.)
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.
Starting Page	203
Ending Page	210
File Size	1923617
Page Count	8
File Format	PDF
ISBN	9781612849355
e-ISBN	9781612849348
e-ISBN	9781612849331
DOI	10.1109/PACIFICVIS.2011.5742391
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Visualization Crime Detection Social network services Terrorism Layout Clustering algorithms Graph Clustering Companies Graph Visualization Financial Visualization
Content Type	Text
Resource Type	Article

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