We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...
We present a novel discriminative approach to parsing inspired by the large-margin criterion underlying support vector machines. Our formulation uses a factorization analogous to ...
Ben Taskar, Dan Klein, Mike Collins, Daphne Koller...
This paper describes an extremely lexicalized probabilistic model for fast and accurate HPSG parsing. In this model, the probabilities of parse trees are defined with only the pro...
In this paper we deal with several kinds of anaphora in unrestricted texts. These kinds of anaphora are pronominal references, surfacecount anaphora and one-anaphora. In order to ...
Abstract Resource adaptlvity" Because the sets of strucNatural language parsing is conceived to be a procedure of disambiguation, which successively reduces an initially total...