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A characterization of the weighted Lovász number based on convex quadratic programming

Overview of attention for article published in Optimization Letters, June 2015
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Title
A characterization of the weighted Lovász number based on convex quadratic programming
Published in
Optimization Letters, June 2015
DOI 10.1007/s11590-015-0911-6
Authors

Carlos J. Luz

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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 24 January 2018.
All research outputs
#18,584,192
of 23,018,998 outputs
Outputs from Optimization Letters
#213
of 444 outputs
Outputs of similar age
#190,719
of 265,217 outputs
Outputs of similar age from Optimization Letters
#3
of 6 outputs
Altmetric has tracked 23,018,998 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 444 research outputs from this source. They receive a mean Attention Score of 0.9. This one is in the 44th percentile – i.e., 44% 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 265,217 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.