Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation conference on Information and knowledge management
A Sequential Pattern Query Language for Supporting Instant Data Mining for e-Services
Proceedings of the 27th International Conference on Very Large Data Bases
Communications of the ACM - A game experience in every application
Evaluating event visualization: a usability study of COPLINK spatio-temporal visualizer
International Journal of Human-Computer Studies
A spatio temporal visualizer for law enforcement
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
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Crime specific event patterns are crucial in detecting potential relationships among suspects in criminal networks. However, current link analysis tools commonly used in detection do not utilize such patterns for detecting various types of crimes. These analysis tools usually provide generic functions for all types of crimes and heavily rely on the user's expertise on the domain knowledge of the crime for successful detection. As a result, they are less effective in detecting patterns in certain crimes. In addition, substantial effort is also required for analyzing vast amount of crime data and visualizing the structural views of the entire criminal network. In order to alleviate these problems, an event-based approach to money laundering data analysis and visualization is proposed in this paper. The effectiveness of the proposed method is demonstrated on a money laundering case from Taiwan.