Parsing citations in biomedical articles using conditional random fields. Zhang, Q., Cao, Y., & Yu, H. Computers in Biology and Medicine, 41(4):190–194, April, 2011. Paper doi abstract bibtex Citations are used ubiquitously in biomedical full-text articles and play an important role for representing both the rhetorical structure and the semantic content of the articles. As a result, text mining systems will significantly benefit from a tool that automatically extracts the content of a citation. In this study, we applied the supervised machine-learning algorithms Conditional Random Fields (CRFs) to automatically parse a citation into its fields (e.g., Author, Title, Journal, and Year). With a subset of html format open-access PubMed Central articles, we report an overall 97.95% F1-score. The citation parser can be accessed at: http://www.cs.uwm.edu/∼qing/projects/cithit/index.html.
@article{zhang_parsing_2011,
title = {Parsing citations in biomedical articles using conditional random fields},
volume = {41},
issn = {00104825},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0010482511000291},
doi = {10.1016/j.compbiomed.2011.02.005},
abstract = {Citations are used ubiquitously in biomedical full-text articles and play an important role for representing both the rhetorical structure and the semantic content of the articles. As a result, text mining systems will significantly benefit from a tool that automatically extracts the content of a citation. In this study, we applied the supervised machine-learning algorithms Conditional Random Fields (CRFs) to automatically parse a citation into its fields (e.g., Author, Title, Journal, and Year). With a subset of html format open-access PubMed Central articles, we report an overall 97.95\% F1-score. The citation parser can be accessed at: http://www.cs.uwm.edu/∼qing/projects/cithit/index.html.},
language = {en},
number = {4},
urldate = {2016-11-30},
journal = {Computers in Biology and Medicine},
author = {Zhang, Qing and Cao, Yong-Gang and Yu, Hong},
month = apr,
year = {2011},
pmid = {21419403 PMCID: PMC3086470},
pages = {190--194},
}
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