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

Source: [Using Centroids of Word Embeddings and Word Mover's Distance for Biomedical Document Retrieval in Question Answering](<https://www.sota2.com/research/paper/68fa62b51e209131ce9faa48>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:24:19.140Z

Authors: Georgios-Ioannis Brokos, Prodromos Malakasiotis, Ion Androutsopoulos

Published: 2016-08-12T20:33:54.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1608.03905>)

[PDF](<https://arxiv.org/pdf/1608.03905.pdf>)