An effective biomedical document classification scheme in support of biocuration: addressing class imbalance-Reference-Cited by-同舟云学术

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An effective biomedical document classification scheme in support of biocuration: addressing class imbalance

Published:2019-01-01 Issue: Volume:2019 Page:
ISSN:1758-0463
Container-title:Database
language:en
Short-container-title:

Author:

Jiang Xiangying¹,Ringwald Martin²,Blake Judith A²,Arighi Cecilia¹³,Zhang Gongbo¹,Shatkay Hagit¹³

Affiliation:

1. Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA

2. The Jackson Laboratory, 600 Main St., Bar Harbor, ME, USA

3. Center of Bioinformatics and Computational Biology, Delaware Biotechnology Institute, Newark, DE, USA

Funder

National Institutes of Health

National Library of Medicine

National Institute of Child Health and Human Development

Publisher

Oxford University Press (OUP)

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Information Systems

Link

http://academic.oup.com/database/article-pdf/doi/10.1093/database/baz045/28526358/baz045.pdf

Reference50 articles.

1. Automatic document classification of biological literature;Chen;BMC Bioinformatics,2006

2. Automatic categorization of diverse experimental information in the bioscience literature;Fang;BMC Bioinformatics,2012

3. Building an efficient curation workflow for the Arabidopsis literature corpus;Li;Database,2012

4. Text mining for the biocuration workflow;Hirschman;Database,2012

5. Machine learning for biomedical literature triage;Almeida;PloS One,2014

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