Ordering information is a critical task for natural language generation applications. In this paper we propose an approach to information ordering that is particularly suited for ...
This paper presents a method to develop a class of variable memory Markov models that have higher memory capacity than traditional (uniform memory) Markov models. The structure of...
This paper presents an open-domain textual Question-Answering system that uses several feedback loops to enhance its performance. These feedback loops combine in a new way statist...
Sanda M. Harabagiu, Dan I. Moldovan, Marius Pasca,...
We define noun phrase translation as a subtask of machine translation. This enables us to build a dedicated noun phrase translation subsystem that improves over the currently bes...
This paper compares two different ways of estimating statistical language models. Many statistical NLP tagging and parsing models are estimated by maximizing the (joint) likelihoo...