Using Centroids of Word Embeddings and Word Mover's Distance for Biomedical Document Retrieval in Question Answering

@inproceedings{Brokos2016UsingCO,
  title={Using Centroids of Word Embeddings and Word Mover's Distance for Biomedical Document Retrieval in Question Answering},
  author={Georgios-Ioannis Brokos and Prodromos Malakasiotis and Ion Androutsopoulos},
  booktitle={BioNLP@ACL},
  year={2016}
}
We propose a document retrieval method for question answering that represents documents and questions as weighted centroids of word embeddings and reranks the retrieved documents with a relaxation of Word Mover’s Distance. Using biomedical questions and documents from BIOASQ, we show that our method is competitive with PUBMED. With a top-k approximation, our method is fast, and easily portable to other domains and languages. 
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