| Title |
Improving protein coreference resolution by simple semantic classification
|
|---|---|
| Published in |
BMC Bioinformatics, November 2012
|
| DOI | 10.1186/1471-2105-13-304 |
| Pubmed ID | |
| Authors |
Ngan Nguyen, Jin-Dong Kim, Makoto Miwa, Takuya Matsuzaki, Junichi Tsujii |
| Abstract |
Current research has shown that major difficulties in event extraction for the biomedical domain are traceable to coreference. Therefore, coreference resolution is believed to be useful for improving event extraction. To address coreference resolution in molecular biology literature, the Protein Coreference (COREF) task was arranged in the BioNLP Shared Task (BioNLP-ST, hereafter) 2011, as a supporting task. However, the shared task results indicated that transferring coreference resolution methods developed for other domains to the biological domain was not a straight-forward task, due to the domain differences in the coreference phenomena. |
X Demographics
The data shown below were collected from the profiles of 2 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 States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| China | 1 | 4% |
| France | 1 | 4% |
| Unknown | 24 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 22% |
| Researcher | 5 | 19% |
| Professor > Associate Professor | 4 | 15% |
| Student > Master | 3 | 11% |
| Professor | 2 | 7% |
| Other | 4 | 15% |
| Unknown | 3 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 52% |
| Agricultural and Biological Sciences | 5 | 19% |
| Engineering | 3 | 11% |
| Neuroscience | 1 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 3 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 30 September 2014.
All research outputs
#13,371,661
of 22,685,926 outputs
Outputs from BMC Bioinformatics
#4,188
of 7,252 outputs
Outputs of similar age
#155,531
of 275,707 outputs
Outputs of similar age from BMC Bioinformatics
#62
of 110 outputs
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We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.