SCAI: Extracting drug-drug interactions using a rich feature vector

Automatic relation extraction provides great support for scientists and database curators in dealing with the extensive amount of biomedical textual data. The DDIExtraction 2013 challenge poses the task of detecting drugdrug interactions and further categorizing them into one of the four relation classes. We present our machine learning system which utilizes lexical, syntactical and semantic based feature sets. Resampling, balancing and ensemble learning experiments are performed to infer the best configuration. For general drugdrug relation extraction, the system achieves 70.4% in F1 score.