A Fast Deep Learning Model for Textual Relevance in Biomedical Information Retrieval

@article{Mohan2018AFD,
  title={A Fast Deep Learning Model for Textual Relevance in Biomedical Information Retrieval},
  author={Sunil Mohan and Nicolas Fiorini and Sun Kim and Zhiyong Lu},
  journal={Proceedings of the 2018 World Wide Web Conference},
  year={2018}
}
Publications in the life sciences are characterized by a large technical vocabulary, with many lexical and semantic variations for expressing the same concept. Towards addressing the problem of relevance in biomedical literature search, we introduce a deep learning model for the relevance of a document's text to a keyword style query. Limited by a relatively small amount of training data, the model uses pre-trained word embeddings. With these, the model first computes a variable-length Delta… 

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