In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the de...
Olivier Y. de Vel, Nianjun Liu, Terry Caelli, Tib&...
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
In the very active field of complex networks, research advances have largely been stimulated by the availability of empirical data and the increase in computational power needed ...
Adrien Friggeri, Guillaume Chelius, Eric Fleury, A...
Background. Software defect prediction has been one of the central topics of software engineering. Predicted defect counts have been used mainly to assess software quality and est...
Thomas Schulz, Lukasz Radlinski, Thomas Gorges, Wo...
— The advance of object tracking technologies leads to huge volumes of spatio-temporal data collected in the form of trajectory data stream. In this study, we investigate the pro...
Lu An Tang, Yu Zheng, Jing Yuan, Jiawei Han, Alice...