Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...
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...
We present a new approach to intrinsic summary evaluation, based on initial experiments in van Halteren and Teufel (2003), which combines two novel aspects: comparison of informat...
The use of centralized, real-time position tracking is proliferating in the areas of logistics and public transportation. Real-time positions can be used to provide up-to-date inf...
At the University of Missouri – Columbia’s Information and Access Technology (IAT) Services, InfoTech Training compares the results of their IT training program with similar t...