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Displaying 1-9 out of 9 total
Mining Exceptional Activity Patterns in Microstructure Data
Found in: Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on
By Yuming Ou, Longbing Cao, Chao Luo, Li Liu
Issue Date:December 2008
pp. 884-887
Market Surveillance plays an important role in maintaining market integrity, transparency and fairness. The existing trading pattern analysis only focuses on interday data which discloses explicit and high-level market dynamics. In the mean time, the exist...
 
Exception Mining on Multiple Time Series in Stock Market
Found in: Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on
By Chao Luo, Yanchang Zhao, Longbing Cao, Yuming Ou, Chengqi Zhang
Issue Date:December 2008
pp. 690-693
This paper presents our research on exception mining on multiple time series data which aims to assist stock market surveillance by identifying market anomalies. Traditional technologies on stock market surveillance have shown their limitations to handle l...
 
Detecting Turning Points of Trading Price and Return Volatility for Market Surveillance Agents
Found in: Web Intelligence and Intelligent Agent Technology, International Conference on
By Yuming Ou, Longbing Cao, Ting Yu, Chengqi Zhang
Issue Date:November 2007
pp. 491-494
Trading agent concept is very useful for trading strategy design and market mechanism design. In this paper, we introduce the use of trading agent for market surveillance. Market surveillance agents can be developed for market surveillance officers and man...
 
Behavior Informatics: A New Perspective
Found in: IEEE Intelligent Systems
By Longbing Cao,Thorsten Joachims,Can Wang,Eric Gaussier,Jinjiu Li,Yuming Ou,Dan Luo,Reza Zafarani,Huan Liu,Guandong Xu,Zhiang Wu,Gabriella Pasi,Ya Zhang,Xiaokang Yang,Hongyuan Zha,Edoardo Serra,V.S. Subrahmanian
Issue Date:July 2014
pp. 62-80
This installment of Trends & Controversies provides an array of perspectives on the latest research in behavior informatics. Longbing Cao introduces the work in "Behavior Informatics: A New Perspective." Then, in "Behavior Computing,...
 
Coupled Behavior Analysis with Applications
Found in: IEEE Transactions on Knowledge and Data Engineering
By Longbing Cao,Yuming Ou,Philip S. Yu
Issue Date:August 2012
pp. 1378-1392
Coupled behaviors refer to the activities of one to many actors who are associated with each other in terms of certain relationships. With increasing network and community-based events and applications, such as group-based crime and social network interact...
 
Identifying Interesting Customers through Web Log Classification
Found in: IEEE Intelligent Systems
By Jeffrey Xu Yu, Yuming Ou, Chengqi Zhang, Shichao Zhang
Issue Date:May 2005
pp. 55-59
Retention recommendation has been an important topic in e-commerce. Subjective classification is a potentially useful approach for both better understanding customer Web logs and identifying information actionable to customer retention. Subjective classifi...
 
Coupled nominal similarity in unsupervised learning
Found in: Proceedings of the 20th ACM international conference on Information and knowledge management (CIKM '11)
By Can Wang, Jinjiu Li, Longbing Cao, Mingchun Wang, Wei Wei, Yuming Ou
Issue Date:October 2011
pp. 973-978
The similarity between nominal objects is not straightforward, especially in unsupervised learning. This paper proposes coupled similarity metrics for nominal objects, which consider not only intra-coupled similarity within an attribute (i.e., value freque...
     
e-NSP: efficient negative sequential pattern mining based on identified positive patterns without database rescanning
Found in: Proceedings of the 20th ACM international conference on Information and knowledge management (CIKM '11)
By Chengqi Zhang, Jinjiu Li, Longbing Cao, Wei Wei, Xiangjun Dong, Yanchang Zhao, Yuming Ou, Zhigang Zheng
Issue Date:October 2011
pp. 825-830
Mining Negative Sequential Patterns (NSP) is much more challenging than mining Positive Sequential Patterns (PSP) due to the high computational complexity and huge search space required in calculating Negative Sequential Candidates (NSC). Very few approach...
     
Detecting abnormal coupled sequences and sequence changes in group-based manipulative trading behaviors
Found in: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '10)
By Gang Wei, Longbing Cao, Philip S. Yu, Yuming Ou
Issue Date:July 2010
pp. 85-94
In capital market surveillance, an emerging trend is that a group of hidden manipulators collaborate with each other to manipulate three trading sequences: buy-orders, sell-orders and trades, through carefully arranging their prices, volumes and time, in o...
     
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