Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Information retrieval systems have to deal with uncertain knowledge and query results should reflect this uncertainty in some manner. However, Semantic Web ontologies are based on...
Combining probability and first-order logic has been the subject of intensive research during the last ten years. The most well-known formalisms combining probability and some sub...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...