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

ACL ID S13-2111
Title SCAI: Extracting drug-drug interactions using a rich feature vector
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

Automatic relation extraction provides great support for scientists and database curators in dealing with the extensive amount of biomed- ical textual data. The DDIExtraction 2013 challenge poses the task of detecting drug- drug 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 en- semble learning experiments are performed to infer the best configuration. For general drug- drug relation extraction, the system achieves 70.4% in F1 score.