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X Demographics
Mendeley readers
Attention Score in Context
| Title |
An effective method of large scale ontology matching
|
|---|---|
| Published in |
Journal of Biomedical Semantics, October 2014
|
| DOI | 10.1186/2041-1480-5-44 |
| Pubmed ID | |
| Abstract |
We are currently facing a proliferation of heterogeneous biomedical data sources accessible through various knowledge-based applications. These data are annotated by increasingly extensive and widely disseminated knowledge organisation systems ranging from simple terminologies and structured vocabularies to formal ontologies. In order to solve the interoperability issue, which arises due to the heterogeneity of these ontologies, an alignment task is usually performed. However, while significant effort has been made to provide tools that automatically align small ontologies containing hundreds or thousands of entities, little attention has been paid to the matching of large sized ontologies in the life sciences domain. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Pakistan | 1 | 2% |
| Unknown | 54 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 29% |
| Student > Master | 9 | 16% |
| Researcher | 5 | 9% |
| Student > Postgraduate | 5 | 9% |
| Other | 3 | 5% |
| Other | 7 | 13% |
| Unknown | 10 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 34 | 62% |
| Engineering | 5 | 9% |
| Agricultural and Biological Sciences | 3 | 5% |
| Social Sciences | 2 | 4% |
| Medicine and Dentistry | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 9 | 16% |
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 26 November 2014.
All research outputs
#13,317,498
of 22,771,140 outputs
Outputs from Journal of Biomedical Semantics
#193
of 364 outputs
Outputs of similar age
#123,263
of 260,387 outputs
Outputs of similar age from Journal of Biomedical Semantics
#6
of 8 outputs
Altmetric has tracked 22,771,140 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 46th percentile – i.e., 46% 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 260,387 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 52% 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 2 of them.