| Title |
Using Workflows to Explore and Optimise Named Entity Recognition for Chemistry
|
|---|---|
| Published in |
PLOS ONE, May 2011
|
| DOI | 10.1371/journal.pone.0020181 |
| Pubmed ID | |
| Authors |
BalaKrishna Kolluru, Lezan Hawizy, Peter Murray-Rust, Junichi Tsujii, Sophia Ananiadou |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 4% |
| United States | 2 | 3% |
| Netherlands | 2 | 3% |
| Germany | 1 | 1% |
| Canada | 1 | 1% |
| Portugal | 1 | 1% |
| China | 1 | 1% |
| Saudi Arabia | 1 | 1% |
| Spain | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 55 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 25% |
| Student > Ph. D. Student | 15 | 22% |
| Other | 6 | 9% |
| Student > Master | 6 | 9% |
| Professor | 5 | 7% |
| Other | 14 | 20% |
| Unknown | 6 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 28 | 41% |
| Agricultural and Biological Sciences | 11 | 16% |
| Chemistry | 6 | 9% |
| Engineering | 5 | 7% |
| Social Sciences | 3 | 4% |
| Other | 9 | 13% |
| Unknown | 7 | 10% |