In recent years, there have been several proposals that extend the expressive power of Bayesian networks with that of relational models. These languages open the possibility for t...
There is increasing interest within the research community in the design and use of recursive probability models. There remains concern about computational complexity costs and th...
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
In the logical approach to information retrieval (IR), retrieval is considered as uncertain inference. Whereas classical IR models are based on propositional logic, we combine Dat...
We argue that groups of unannotated texts with overlapping and non-contradictory semantics represent a valuable source of information for learning semantic representations. A simp...