Learning to reformulate long queries for clinical decision support-Reference-Cited by-同舟云学术

Learning to reformulate long queries for clinical decision support

Published:2017-09-14 Issue:11 Volume:68 Page:2602-2619
ISSN:2330-1635
Container-title:Journal of the Association for Information Science and Technology
language:en
Short-container-title:Journal of the Association for Information Science and Technology

Author:

Soldaini Luca¹^ORCID,Yates Andrew²,Goharian Nazli¹

Affiliation:

1. Information Retrieval Lab, Georgetown UniversityWashington DC USA

2. Max Planck Institute for Informatics, Saarland Informatics CampusSaarbruecken Germany

Funder

National Science Foundation

Publisher

Wiley

Subject

Library and Information Sciences,Information Systems and Management,Computer Networks and Communications,Information Systems

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/asi.23924

Reference87 articles.

1. Searching in Medline: Query expansion and manual indexing evaluation

2. Probabilistic models of information retrieval based on measuring the divergence from randomness

3. An overview of MetaMap: historical perspective and recent advances

4. Balaneshin Kordan S. Kotov A. &Xisto R.(2015). WSU‐IR at TREC 2015 clinical decision support track: Joint weighting of explicit and latent medical query concepts from diverse sources. In Proceedings of the 2015 Text Retrieval Conference.

5. Bedrick S. &Sheikshabbafghi G.(2013). Lucene metamap and language modeling: OHSU at CLEF ehealth 2013. In CLEF (Working Notes).

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