In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...
In this paper, we present a method that improves Japanese dependency parsing by using large-scale statistical information. It takes into account two kinds of information not consi...
In this paper, we describe our hybrid parsing model on Mandarin Chinese processing. The model combines the mainstream constitute and dependency parsing and the dataset we use it t...
We describe our experiments using the DeSR parser in the multilingual and domain adaptation tracks of the CoNLL 2007 shared task. DeSR implements an incremental deterministic Shif...
Giuseppe Attardi, Felice dell'Orletta, Maria Simi,...
The Conference on Computational Natural Language Learning features a shared task, in which participants train and test their learning systems on the same data sets. In 2007, as in...