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Mendeley readers
Attention Score in Context
Title |
Clustering cliques for graph-based summarization of the biomedical research literature
|
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Published in |
BMC Bioinformatics, June 2013
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DOI | 10.1186/1471-2105-14-182 |
Pubmed ID | |
Authors |
Han Zhang, Marcelo Fiszman, Dongwook Shin, Bartlomiej Wilkowski, Thomas C Rindflesch |
Abstract |
Graph-based notions are increasingly used in biomedical data mining and knowledge discovery tasks. In this paper, we present a clique-clustering method to automatically summarize graphs of semantic predications produced from PubMed citations (titles and abstracts). |
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 % |
---|---|---|
Chile | 1 | 50% |
United States | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 4% |
Brazil | 1 | 1% |
Canada | 1 | 1% |
Iran, Islamic Republic of | 1 | 1% |
Australia | 1 | 1% |
Denmark | 1 | 1% |
Slovenia | 1 | 1% |
Japan | 1 | 1% |
Russia | 1 | 1% |
Other | 0 | 0% |
Unknown | 57 | 84% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 19 | 28% |
Researcher | 16 | 24% |
Student > Master | 5 | 7% |
Student > Doctoral Student | 4 | 6% |
Student > Bachelor | 4 | 6% |
Other | 15 | 22% |
Unknown | 5 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 22 | 32% |
Agricultural and Biological Sciences | 10 | 15% |
Medicine and Dentistry | 6 | 9% |
Engineering | 4 | 6% |
Biochemistry, Genetics and Molecular Biology | 3 | 4% |
Other | 15 | 22% |
Unknown | 8 | 12% |
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 30 July 2015.
All research outputs
#15,866,607
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#5,477
of 7,400 outputs
Outputs of similar age
#123,908
of 199,097 outputs
Outputs of similar age from BMC Bioinformatics
#72
of 101 outputs
Altmetric has tracked 23,577,654 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 7,400 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 17th percentile – i.e., 17% 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 199,097 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.