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Corpus annotation for mining biomedical events from literature

Overview of attention for article published in BMC Bioinformatics, January 2008
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

wikipedia
2 Wikipedia pages

Citations

dimensions_citation
182 Dimensions

Readers on

mendeley
195 Mendeley
citeulike
21 CiteULike
connotea
3 Connotea
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Title
Corpus annotation for mining biomedical events from literature
Published in
BMC Bioinformatics, January 2008
DOI 10.1186/1471-2105-9-10
Pubmed ID
Authors

Jin-Dong Kim, Tomoko Ohta, Jun'ichi Tsujii

Abstract

Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation.

Mendeley readers

The data shown below were compiled from readership statistics for 195 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 19 10%
United Kingdom 5 3%
France 2 1%
Portugal 2 1%
Spain 2 1%
Netherlands 1 <1%
Italy 1 <1%
Malaysia 1 <1%
Colombia 1 <1%
Other 7 4%
Unknown 154 79%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 21%
Student > Ph. D. Student 35 18%
Student > Master 32 16%
Professor > Associate Professor 17 9%
Professor 12 6%
Other 40 21%
Unknown 18 9%
Readers by discipline Count As %
Computer Science 83 43%
Agricultural and Biological Sciences 32 16%
Medicine and Dentistry 17 9%
Linguistics 11 6%
Biochemistry, Genetics and Molecular Biology 9 5%
Other 19 10%
Unknown 24 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 June 2015.
All research outputs
#1,322,076
of 5,273,623 outputs
Outputs from BMC Bioinformatics
#1,132
of 2,966 outputs
Outputs of similar age
#57,069
of 188,759 outputs
Outputs of similar age from BMC Bioinformatics
#51
of 132 outputs
Altmetric has tracked 5,273,623 research outputs across all sources so far. This one has received more attention than most of these and is in the 63rd percentile.
So far Altmetric has tracked 2,966 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 188,759 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.