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• W2022709849 abstract "Objective: We present a new software system, VisFAN, for the visual analysis of financial activity networks. We combine enhanced graph drawing techniques to devise novel algorithms and interaction functionalities for the visual exploration of networked data sets, together with tools for SNA and for the automatic generation of reports. An application example constructed on real data is presented. We also report the results of a study aimed at qualitatively understanding the satisfaction level of the analysts when using VisFAN. VisFAN makes a strong use of visual interactive tools, combined with ad-hoc clustering techniques and customizable layout constraints management. As this system confirms, information visualization can play a crucial role to face the discovery of financial crimes." @default.
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• W2022709849 date "2014-08-01" @default.
• W2022709849 modified "2023-10-13" @default.
• W2022709849 title "Network visualization for financial crime detection" @default.
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• W2022709849 doi "https://doi.org/10.1016/j.jvlc.2014.01.002" @default.
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