We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
This paper provides evidence that the use of more unlabeled data in semi-supervised learning can improve the performance of Natural Language Processing (NLP) tasks, such as part-o...
In our participation to the 2010 LogCLEF track we focused on the analysis of the European Library (TEL) logs and in particular we experimented with the identification of the natura...
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
We report the results of an experiment to assess the ability of automated MT evaluation metrics to remain sensitive to variations in MT quality as the average quality of the compa...