Abstract. Outlier detection has been used for centuries to detect and, where appropriate, remove anomalous observations from data. Outliers arise due to mechanical faults, changes ...
This paper describes our experience with applying data mining techniques to the problem of fraud detection in spatio-temporal health data in Medicare Australia. A modular framework...
Kee Siong Ng, Yin Shan, D. Wayne Murray, Alison Su...
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Atypical behaviours are the basis of a valuable knowledge in domains related to security (e.g. fraud detection for credit card [1], cyber security [4] or safety of critical systems...
Several new Complex Event Processing (CEP) engines have been recently released, many of which are intended to be used in performance sensitive scenarios - like fraud detection, tr...
Marcelo R. N. Mendes, Pedro Bizarro, Paulo Marques