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Optimising chemical named entity recognition with pre-processing analytics, knowledge-rich features and heuristics

Overview of attention for article published in Journal of Cheminformatics, January 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
56 Mendeley
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Title
Optimising chemical named entity recognition with pre-processing analytics, knowledge-rich features and heuristics
Published in
Journal of Cheminformatics, January 2015
DOI 10.1186/1758-2946-7-s1-s6
Pubmed ID
Authors

Riza Batista-Navarro, Rafal Rak, Sophia Ananiadou

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 4%
Croatia 1 2%
Brazil 1 2%
Unknown 52 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 27%
Researcher 12 21%
Student > Master 8 14%
Student > Bachelor 7 13%
Student > Doctoral Student 3 5%
Other 5 9%
Unknown 6 11%
Readers by discipline Count As %
Computer Science 29 52%
Engineering 4 7%
Chemistry 4 7%
Agricultural and Biological Sciences 3 5%
Decision Sciences 2 4%
Other 6 11%
Unknown 8 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 16 March 2015.
All research outputs
#2,513,503
of 13,862,299 outputs
Outputs from Journal of Cheminformatics
#252
of 559 outputs
Outputs of similar age
#52,247
of 280,372 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 1 outputs
Altmetric has tracked 13,862,299 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 559 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has gotten more attention than average, scoring higher than 54% 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 280,372 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them