document: Applying data mining in investigating money laundering crimes In this paper , we study the problem of applying data mining to facilitate the investigation of money laundering crimes ( MLCs ) . We have identified a new paradigm of problems -- that of automatic community generation based on uni-party data , the data in which there is no direct or explicit link information available . Consequently , we have proposed a new methodology for Link Discovery based on Correlation Analysis ( LDCA ) . We have used MLC group model generation as an exemplary application of this problem paradigm , and have focused on this application to develop a specific method of automatic MLC group model generation based on timeline analysis using the LDCA methodology , called CORAL . A prototype of CORAL method has been implemented , and preliminary testing and evaluations based on a real MLC case data are reported . The contributions of this work are : ( 1 ) identification of the uni-party data community generation problem paradigm , ( 2 ) proposal of a new methodology LDCA to solve for problems in this paradigm , ( 3 ) formulation of the MLC group model generation problem as an example of this paradigm , ( 4 ) application of the LDCA methodology in developing a specific solution ( CORAL ) to the MLC group model generation problem , and ( 5 ) development , evaluation , and testing of the CORAL prototype in a real MLC case data .
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