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Divide-and-Conquer Algorithms for Partitioning Hypergraphs and Submodular Systems

Overview of attention for article published in Algorithmica, December 2010
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Mentioned by

q&a
1 Q&A thread

Citations

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12 Dimensions

Readers on

mendeley
15 Mendeley
Title
Divide-and-Conquer Algorithms for Partitioning Hypergraphs and Submodular Systems
Published in
Algorithmica, December 2010
DOI 10.1007/s00453-010-9483-0
Authors

Kazumasa Okumoto, Takuro Fukunaga, Hiroshi Nagamochi

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 4 27%
Student > Master 3 20%
Student > Ph. D. Student 3 20%
Student > Doctoral Student 2 13%
Other 1 7%
Other 2 13%
Readers by discipline Count As %
Computer Science 7 47%
Mathematics 2 13%
Engineering 2 13%
Agricultural and Biological Sciences 1 7%
Economics, Econometrics and Finance 1 7%
Other 1 7%
Unknown 1 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 06 June 2016.
All research outputs
#12,960,084
of 22,876,619 outputs
Outputs from Algorithmica
#301
of 419 outputs
Outputs of similar age
#133,298
of 182,377 outputs
Outputs of similar age from Algorithmica
#2
of 4 outputs
Altmetric has tracked 22,876,619 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 419 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 24th percentile – i.e., 24% 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 182,377 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.