Automatic sentence classifier using sentence ordering features for Event Based Medicine: Shared task system description

摘要

In this paper, we propose an automatic sentence classification model that can map sentences of a given biomedical abstract into set of pre-defined categories which are used for Evidence Based Medicine (EBM). In our model we explored the use of various lexical, structural and sequential features and worked with Conditional Random Fields (CRF) for classification. Results obtained with our proposed method show improvement with respect to current state-of-the-art systems. We have participated in the ALTA shared task 2012 and our best performing model is ranked among top 5 systems.