[1] Masciandaro,Donato,Raffaella. Worldwide anti-money laundering regulation:estimating costs and benefits[R]. “Paolo Baffi” Center on Centural Banking and Financial Regulation,2008:12-13.
[2] 中国人民共和国中央人民政府国务院. 中国2008—2012年反洗钱战略[R]. 北京:中国人民银行,2009.
[3] 唐旭,师永彦,曹作义. 中国反洗钱工作有效性研究[J]. 金融研究,2009 (8):1-16.
[4] Henzinger M R,Raghavan P,Rajagopalan S. Computing on data streams[R]. Technical Report,1998(50):107-118.
[5] 杨胜刚,何静. 反洗钱领域大额与可疑交易信息报告制度的经济学分析[J]. 金融研究,2004(10):115-117.
[6] 杨胜刚,何靖,肖翼. 反洗钱中监管机构和商业银行的博弈与委托代理问题研究[J]. 金融研究,2007(1):71-83.
[7] 李时. 基于模糊概念的可疑金融交易量化关联规则研究[J]. 当代经济科学,2007(5):28-31.
[8] 张成虎,赵小虎. 基于决策树算法的反洗钱识别研究[J]. 武汉理工大学学报:自然科学版,2008(2):154-156.
[9] Menon R,Kuman S. Understanding the role of technology in anti-money laundering compliance[R]. Infosys Technology Ltd,2005 (1):2-13.
[10] 欧阳卫民. 金融情报机构[M]. 北京:中国金融出版社,2005:112-117.
[11] 欧阳卫民. 大额和可疑资金交易监测分析实务[M]. 北京:法律出版社,2006:253-259.
[12] 孙景,张成虎,陈善新. 基于时间序列孤立点检测的可疑外汇资金交易识别研究[J]. 统计与决策,2010(18):26-29.
[13] 王斌,汤俊,陶也青.一种基于混沌预测的离群时间序列检测方法[J]. 武汉大学学报:工学版,2010,43(2):265-268.
[14] Liu X. A scan statistics based suspicious transactions detection model for anti-money laundering(AML) in financial institutions[C]. Proceeding of Multimedia Communications (Mediacom) International Conference,2010:210-213.
[15] Liu K Y. An improved support-vector network model for anti-money laundering[C]. Proceeding of 5th Management of e-Commerce and e-Government (ICMeCG) International Conference,2011:193-196.
[16] 侯东风,张维明,刘青宝. 基于兴趣视图子集的流立方体计算方法[J]. 计算机研究与发展,2011,48(12):2369-2378.
[17] 袁正午,程宇翔,梁均军. 一种高效流立方体结构[J]. 计算机工程与应用,2011,47(17):140-144.
[18] Han J W,Jian P. Mining frequent patterns without candidate generation:a frequent-pattern tree approach[J]. Data Mining and Knowledge Discovery,2004,8(1):53-87.
[19] Chi Y,Wang H X,Philip S. Catch the moment:maintaining closed frequent item sets over a data stream sliding window[J]. Knowledge an Information Systems,2006,10(3):265-294.
[20] Fang M,Shivakumar N. Computing iceberg queries efficiently[C]. Proceeding of the 24th VLDB Conference,1998:299-310.
[21] Beyer K,Ramakrishnan R. Bottom-up computation of spares and iceberg cubes[J]. ACM SIGMOD Record,1999,28(2):359-
[22] Xin D,Han J W,Li X,et al. Star-cubing:computing iceberg cubes by top-down and bottom-up integration[C]. Proceeding of the 29th VLDB Conference,2003:476-487.
[23] Chen Y X,Dong G Z,Han J W,et al. Multidimensional regression analysis of time series data streams[C]. Proceeding of the 28th VLDB Conference,2002:323-334.
[24] Han J W. Stream cube:an architecture for multidimensional analysis of data streams[J]. Distributed and Parallel Databases,2005,18(2):173-197.
[25] Hershberger J,Shrivastava N,Suri S. Adaptive spatial partitioning for multidimensional data sreams[J]. Algorithmica,2006,46(1):97-117.
[26] .
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