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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FlexiTerm: a flexible term recognition method
|
|---|---|
| Published in |
Journal of Biomedical Semantics, October 2013
|
| DOI | 10.1186/2041-1480-4-27 |
| Pubmed ID | |
| Authors |
Irena Spasić, Mark Greenwood, Alun Preece, Nick Francis, Glyn Elwyn |
| Abstract |
The increasing amount of textual information in biomedicine requires effective term recognition methods to identify textual representations of domain-specific concepts as the first step toward automating its semantic interpretation. The dictionary look-up approaches may not always be suitable for dynamic domains such as biomedicine or the newly emerging types of media such as patient blogs, the main obstacles being the use of non-standardised terminology and high degree of term variation. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| France | 1 | <1% |
| Netherlands | 1 | <1% |
| Mexico | 1 | <1% |
| Spain | 1 | <1% |
| Unknown | 107 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 30 | 27% |
| Student > Ph. D. Student | 14 | 12% |
| Researcher | 11 | 10% |
| Student > Bachelor | 5 | 4% |
| Other | 5 | 4% |
| Other | 9 | 8% |
| Unknown | 39 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 31 | 27% |
| Arts and Humanities | 10 | 9% |
| Linguistics | 6 | 5% |
| Agricultural and Biological Sciences | 5 | 4% |
| Social Sciences | 5 | 4% |
| Other | 13 | 12% |
| Unknown | 43 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 19 October 2013.
All research outputs
#19,935,717
of 25,394,764 outputs
Outputs from Journal of Biomedical Semantics
#291
of 368 outputs
Outputs of similar age
#160,704
of 222,863 outputs
Outputs of similar age from Journal of Biomedical Semantics
#15
of 16 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 222,863 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.