About CliNER CliNER is a command line tool for identification of mentions of four categories of clinically relevant events: Problems, Tests, Treatments and Clinical Departments. It also recognises and normalises clinical temporal expressions. It was developed as part of the i2b2 2012 text mining challenge and therefore has been trained…
Contrasts and contradictions in scientific texts
Detecting and analysing contrasts and contradictions in scientific texts is essential for suggesting further research potentials and discoveries. Finding contrasts and contradictions in text by means of automatic methods is a relatively new area in text mining. Specifically, most biological text mining research has so far focused on mining affirmative…
Information for prospective postgraduate students
Training
gnTEAM provides traninig in topics related to text mining for undergraduate (BSc final year projects) and postgraudate students (MSc, MPhil, PhD and EngD projects). Final year undergraduate and MSc projects associated with the team are announced annually as part of the School of Computer Science taught programmes. The current research post-graduate…