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

Georgios-Ioannis Brokos, Prodromos Malakasiotis, Ion Androutsopoulos · 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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