Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
We investigate the problem of ordering medical events in unstructured clinical narratives by learning to rank them based on their time of occurrence. We represent each medical eve...
Preethi Raghavan, Albert M. Lai, Eric Fosler-Lussi...
We consider that factors such as prosody of systems’ utterances and dialogue rhythm are important to attain a natural human-machine dialogue. However, the relations between dialo...
Research on information extraction (IE) seeks to distill relational tuples from natural language text, such as the contents of the WWW. Most IE work has focussed on identifying st...
The goal of our work is to improve the Natural Language feedback provided by Intelligent Tutoring Systems. In this paper, we discuss how to make the content presented by one such ...