WBI-DDI: Drug-Drug Interaction Extraction using Majority Voting

@inproceedings{Thomas2013WBIDDIDI,
  title={WBI-DDI: Drug-Drug Interaction Extraction using Majority Voting},
  author={Philippe Thomas and Mariana L. Neves and Tim Rockt{\"a}schel and Ulf Leser},
  booktitle={SemEval@NAACL-HLT},
  year={2013}
}
This work describes the participation of the WBI-DDI team on the SemEval 2013 – Task 9.2 DDI extraction challenge. The task consisted of extracting interactions between pairs of drugs from two collections of documents (DrugBank and MEDLINE) and their classification into four subtypes: advise, effect, mechanism, and int. We developed a two-step approach in which pairs are initially extracted using ensembles of up to five different classifiers and then relabeled to one of the four categories. Our… CONTINUE READING
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