Abstract—We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in ...
Wei Xu, Ling Huang, Armando Fox, David Patterson, ...
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
In this paper, we propose a novel framework called SmartMiner for web usage mining problem which uses link information for producing accurate user sessions and frequent navigation...
Murat Ali Bayir, Ismail Hakki Toroslu, Ahmet Cosar...
The number of mentally ill people is increasing globally each year. Despite major medical advances, the identification of genetic and environmental factors responsible for mental ...
Time series motif discovery is an important problem with applications in a variety of areas that range from telecommunications to medicine. Several algorithms have been proposed t...