Using Centroids of Word Embeddings and Word Mover's Distance for   Biomedical Document Retrieval in Question Answering
  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. 
Georgios-Ioannis Brokos, Prodromos Malakasiotis and Ion   Androutsopoulos
cs.IR