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KDD
2003
ACM
266views Data Mining» more  KDD 2003»
14 years 8 months ago
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 --- th...
Zhongfei (Mark) Zhang, John J. Salerno, Philip S. ...
IJCAI
2007
13 years 9 months ago
Learning to Identify Unexpected Instances in the Test Set
Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
Xiaoli Li, Bing Liu, See-Kiong Ng
CONSTRAINTS
2008
117views more  CONSTRAINTS 2008»
13 years 7 months ago
Domain Specific High-Level Constraints for User Interface Layout
We present the Auckland Layout Model (ALM), a constraint-based technique for specifying 2D layout as it is used for arranging the controls in a GUI. Most GUI frameworks offer layo...
Christof Lutteroth, Robert Strandh, Gerald Weber
IJKDB
2010
170views more  IJKDB 2010»
13 years 4 months ago
Clustering Genes Using Heterogeneous Data Sources
Clustering of gene expression data is a standard exploratory technique used to identify closely related genes. Many other sources of data are also likely to be of great assistance...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...
CORR
2010
Springer
173views Education» more  CORR 2010»
13 years 5 months ago
Mining Multi-Level Frequent Itemsets under Constraints
Mining association rules is a task of data mining, which extracts knowledge in the form of significant implication relation of useful items (objects) from a database. Mining multi...
Mohamed Salah Gouider, Amine Farhat