Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
This work addresses the issue of prioritized reasoning in the context of logic programming. The case of preference conditions involving atoms is considered and a refinement of th...
Abstract. In this paper, we present a revision strategy of revising a conditional probabilistic logic program (PLP) when new information is received (which is in the form of probab...
The traditional mention-pair model for coreference resolution cannot capture information beyond mention pairs for both learning and testing. To deal with this problem, we present ...
Xiaofeng Yang, Jian Su, Jun Lang, Chew Lim Tan, Ti...
This paper presents and evaluates an original approach to automatically align bitexts at the word level. It relies on a syntactic dependency analysis of the source and target text...