We propose a multi-sensor affect recognition system and evaluate it on the challenging task of classifying interest (or disinterest) in children trying to solve an educational pu...
In this paper we present a system for automatically integrating unstructured text into a multi-relational database using state-of-the-art statistical models for structure extracti...
Many real-world classification tasks involve the prediction of multiple, inter-dependent class labels. A prototypical case of this sort deals with prediction of a sequence of labe...
Statistical machine learning methods are employed to train a Named Entity Recognizer from annotated data. Methods like Maximum Entropy and Conditional Random Fields make use of fe...
Named Entity Recognition (NER) is the task of locating and classifying names in text. In previous work, NER was limited to a small number of predefined entity classes (e.g., peop...