Large-scale systems for information extraction include many different classifiers and extractors. Experience in building such systems shows that finding an appropriate architect...
Abstract. Group comparison per se is a fundamental task in many scientific endeavours but is also the basis of any classifier. Contrast sets and emerging patterns contrast betwee...
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...
The wavelet transform has been used for feature extraction in many applications of pattern recognition. However, in general the learning algorithms are not designed taking into acc...
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...