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U-Compare bio-event meta-service: compatible BioNLP event extraction services

Overview of attention for article published in BMC Bioinformatics, December 2011
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2 X users

Citations

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Title
U-Compare bio-event meta-service: compatible BioNLP event extraction services
Published in
BMC Bioinformatics, December 2011
DOI 10.1186/1471-2105-12-481
Pubmed ID
Authors

Yoshinobu Kano, Jari Björne, Filip Ginter, Tapio Salakoski, Ekaterina Buyko, Udo Hahn, K Bretonnel Cohen, Karin Verspoor, Christophe Roeder, Lawrence E Hunter, Halil Kilicoglu, Sabine Bergler, Sofie Van Landeghem, Thomas Van Parys, Yves Van de Peer, Makoto Miwa, Sophia Ananiadou, Mariana Neves, Alberto Pascual-Montano, Arzucan Özgür, Dragomir R Radev, Sebastian Riedel, Rune Sætre, Hong-Woo Chun, Jin-Dong Kim, Sampo Pyysalo, Tomoko Ohta, Jun'ichi Tsujii

Abstract

Bio-molecular event extraction from literature is recognized as an important task of bio text mining and, as such, many relevant systems have been developed and made available during the last decade. While such systems provide useful services individually, there is a need for a meta-service to enable comparison and ensemble of such services, offering optimal solutions for various purposes.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 4%
France 2 4%
United States 2 4%
Spain 2 4%
United Kingdom 2 4%
Australia 1 2%
Brazil 1 2%
China 1 2%
Unknown 36 73%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Ph. D. Student 7 14%
Professor > Associate Professor 5 10%
Student > Doctoral Student 4 8%
Student > Master 4 8%
Other 13 27%
Unknown 6 12%
Readers by discipline Count As %
Computer Science 24 49%
Agricultural and Biological Sciences 8 16%
Mathematics 2 4%
Medicine and Dentistry 2 4%
Engineering 2 4%
Other 4 8%
Unknown 7 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 December 2011.
All research outputs
#15,239,825
of 22,659,164 outputs
Outputs from BMC Bioinformatics
#5,353
of 7,240 outputs
Outputs of similar age
#162,712
of 242,864 outputs
Outputs of similar age from BMC Bioinformatics
#67
of 100 outputs
Altmetric has tracked 22,659,164 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,240 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 242,864 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.