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Mendeley readers
Attention Score in Context
| Title |
A generalizable NLP framework for fast development of pattern-based biomedical relation extraction systems
|
|---|---|
| Published in |
BMC Bioinformatics, August 2014
|
| DOI | 10.1186/1471-2105-15-285 |
| Pubmed ID | |
| Authors |
Yifan Peng, Manabu Torii, Cathy H Wu, K Vijay-Shanker |
| Abstract |
Text mining is increasingly used in the biomedical domain because of its ability to automatically gather information from large amount of scientific articles. One important task in biomedical text mining is relation extraction, which aims to identify designated relations among biological entities reported in literature. A relation extraction system achieving high performance is expensive to develop because of the substantial time and effort required for its design and implementation. Here, we report a novel framework to facilitate the development of a pattern-based biomedical relation extraction system. It has several unique design features: (1) leveraging syntactic variations possible in a language and automatically generating extraction patterns in a systematic manner, (2) applying sentence simplification to improve the coverage of extraction patterns, and (3) identifying referential relations between a syntactic argument of a predicate and the actual target expected in the relation extraction task. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 20% |
| Norway | 1 | 20% |
| Canada | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| Netherlands | 1 | 2% |
| Spain | 1 | 2% |
| France | 1 | 2% |
| Japan | 1 | 2% |
| Poland | 1 | 2% |
| Unknown | 45 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 27% |
| Researcher | 9 | 17% |
| Student > Master | 7 | 13% |
| Student > Doctoral Student | 5 | 10% |
| Student > Bachelor | 5 | 10% |
| Other | 7 | 13% |
| Unknown | 5 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 28 | 54% |
| Agricultural and Biological Sciences | 7 | 13% |
| Biochemistry, Genetics and Molecular Biology | 4 | 8% |
| Medicine and Dentistry | 3 | 6% |
| Linguistics | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 6 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 24 January 2016.
All research outputs
#6,272,839
of 22,761,738 outputs
Outputs from BMC Bioinformatics
#2,395
of 7,273 outputs
Outputs of similar age
#60,906
of 235,668 outputs
Outputs of similar age from BMC Bioinformatics
#45
of 114 outputs
Altmetric has tracked 22,761,738 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 66% 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 235,668 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 73% of its contemporaries.
We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.