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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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Mentioned by

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2 tweeters

Citations

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10 Dimensions

Readers on

mendeley
45 Mendeley
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2 CiteULike
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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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 45 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%
Spain 2 4%
United Kingdom 2 4%
United States 2 4%
China 1 2%
Australia 1 2%
Brazil 1 2%
Unknown 32 71%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 22%
Student > Ph. D. Student 7 16%
Student > Doctoral Student 4 9%
Professor > Associate Professor 4 9%
Student > Master 4 9%
Other 12 27%
Unknown 4 9%
Readers by discipline Count As %
Computer Science 23 51%
Agricultural and Biological Sciences 7 16%
Engineering 2 4%
Medicine and Dentistry 2 4%
Mathematics 2 4%
Other 3 7%
Unknown 6 13%

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
#7,762,553
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,176
of 4,576 outputs
Outputs of similar age
#116,968
of 221,338 outputs
Outputs of similar age from BMC Bioinformatics
#122
of 175 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% 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 221,338 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 175 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.