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

Understand

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.