Intuitive and meaningful interpretation of geographical phenomena requires their representation at multiple levels of detail. This is due to the scale dependent nature of their pr...
Bayesian networks (BNs) have been widely used as a model for knowledge representation and probabilistic inferences. However, the single probability representation of conditional d...
We discuss the application of Model-Based Diagnosis in (agent-based) planning. Here, a plan together with its executing agent is considered as a system to be diagnosed. It is assum...
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
This paper presents a parse-and-paraphrase paradigm to assess the degrees of sentiment for product reviews. Sentiment identification has been well studied; however, most previous ...