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Systematic Characterizations of Text Similarity in Full Text Biomedical Publications

Overview of attention for article published in PLOS ONE, September 2010
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8 CiteULike
Title
Systematic Characterizations of Text Similarity in Full Text Biomedical Publications
Published in
PLOS ONE, September 2010
DOI 10.1371/journal.pone.0012704
Pubmed ID
Authors

Zhaohui Sun, Mounir Errami, Tara Long, Chris Renard, Nishant Choradia, Harold Garner

Abstract

Computational methods have been used to find duplicate biomedical publications in MEDLINE. Full text articles are becoming increasingly available, yet the similarities among them have not been systematically studied. Here, we quantitatively investigated the full text similarity of biomedical publications in PubMed Central.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 3 4%
Mexico 2 2%
France 1 1%
Australia 1 1%
Czechia 1 1%
Germany 1 1%
Brazil 1 1%
United Kingdom 1 1%
Unknown 71 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 29%
Other 14 17%
Student > Ph. D. Student 9 11%
Student > Bachelor 7 9%
Professor > Associate Professor 6 7%
Other 14 17%
Unknown 8 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 24%
Medicine and Dentistry 17 21%
Computer Science 14 17%
Biochemistry, Genetics and Molecular Biology 5 6%
Physics and Astronomy 3 4%
Other 13 16%
Unknown 10 12%