Discriminative learning methods are widely used in natural language processing. These methods work best when their training and test data are drawn from the same distribution. For...
Current statistical parsers tend to perform well only on their training domain and nearby genres. While strong performance on a few related domains is sufficient for many situatio...
Abstract. This paper describes a method of adapting a domain-independent HPSG parser to a biomedical domain. Without modifying the grammar and the probabilistic model of the origin...
In this paper, we demonstrate that the main standard optimization techniques dependency directed backtracking and model merging can be adapted to description logics with concrete ...
Abstract. This paper presents a knowledge-based approach to eLearning, where the domain ontology plays central role as a resource structuring the learning content and supporting ï¬...
Galia Angelova, Ognian Kalaydjiev, Albena Strupcha...