This paper presents results from analyzing the vulnerability of security-critical software applications to malicious threats and anomalous events using an automated fault injectio...
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
The goal of sentiment prediction is to automatically identify whether a given piece of text expresses positive or negative opinion towards a topic of interest. One can pose sentim...
This paper describes the development of a predictive model for corporate insolvency risk in Australia. The model building methodology is empirical with out-ofsample future year te...
The so-called noise-component has been introduced by Banfield and Raftery (1993) to improve the robustness of cluster analysis based on the normal mixture model. The idea is to ad...