Knowledge discovery on social network data can uncover latent social trends and produce valuable findings that benefit the welfare of the general public. A growing amount of resea...
We present an objective approach for evaluating probability elicitation methods in probabilistic models. Our method draws on ideas from research on learning Bayesian networks: if ...
Abstract. While the discovery of structural variants in the human population is ongoing, most methods for this task assume that the genome is sequenced to high coverage (e.g. 40x),...
The extraction of temporal characteristics from sensor data streams can reveal important properties about the sensed events. Knowledge of temporal characteristics in applications ...
: This paper presents an approach to model ontologies for the e-Government domain as a basis for an integrated e-Government environment. Over the last couple of years the applicati...