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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deploying and sharing U-Compare workflows as web services
|
|---|---|
| Published in |
Journal of Biomedical Semantics, February 2013
|
| DOI | 10.1186/2041-1480-4-7 |
| Pubmed ID | |
| Authors |
Georgios Kontonatsios, Ioannis Korkontzelos, BalaKrishna Kolluru, Paul Thompson, Sophia Ananiadou |
| Abstract |
U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. Users can rapidly develop biomedical text mining workflows by mixing and matching U-Compare's components. Workflows developed using U-Compare can be exported and sent to other users who, in turn, can import and re-use them. However, the resulting workflows are standalone applications, i.e., software tools that run and are accessible only via a local machine, and that can only be run with the U-Compare platform. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 63% |
| Italy | 1 | 13% |
| Korea, Republic of | 1 | 13% |
| Unknown | 1 | 13% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 5% |
| Netherlands | 1 | 3% |
| Germany | 1 | 3% |
| Canada | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 34 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 33% |
| Student > Ph. D. Student | 7 | 18% |
| Student > Master | 6 | 15% |
| Other | 4 | 10% |
| Student > Bachelor | 3 | 8% |
| Other | 4 | 10% |
| Unknown | 3 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 43% |
| Agricultural and Biological Sciences | 7 | 18% |
| Engineering | 4 | 10% |
| Environmental Science | 1 | 3% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 5 | 13% |
| Unknown | 5 | 13% |
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 21 March 2014.
All research outputs
#5,399,661
of 25,371,288 outputs
Outputs from Journal of Biomedical Semantics
#79
of 368 outputs
Outputs of similar age
#42,999
of 204,435 outputs
Outputs of similar age from Journal of Biomedical Semantics
#4
of 8 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 78% 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 204,435 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 78% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.