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Research on Money Laundering Detection Based on Improved Minimum Spanning Tree Clustering and Its Application

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2 Author(s)
Xingqi Wang ; Sch. of Comput. Sci., Hangzhou Dianzi Univ. (HDU), Hangzhou, China ; Guang Dong

To detect suspicious money laundering transaction in the real world financial applications, a new dissimilarity metric was proposed and a novel money laundering detection algorithm based on improved minimum spanning tree clustering was put forward in this paper. Suspicious money laundering transaction detection experiment on financial data set from the real world indicates that our algorithm is effective and succinct.

Published in:

Knowledge Acquisition and Modeling, 2009. KAM '09. Second International Symposium on  (Volume:2 )

Date of Conference:

Nov. 30 2009-Dec. 1 2009