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Criss-cross methods: A fresh view on pivot algorithms

Overview of attention for article published in Mathematical Programming, October 1997
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Mentioned by

wikipedia
14 Wikipedia pages

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
29 Mendeley
citeulike
2 CiteULike
Title
Criss-cross methods: A fresh view on pivot algorithms
Published in
Mathematical Programming, October 1997
DOI 10.1007/bf02614325
Authors

Komei Fukuda, Tamás Terlaky

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Switzerland 1 3%
Unknown 27 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 28%
Researcher 3 10%
Student > Bachelor 3 10%
Student > Master 2 7%
Student > Doctoral Student 1 3%
Other 5 17%
Unknown 7 24%
Readers by discipline Count As %
Computer Science 8 28%
Engineering 8 28%
Mathematics 2 7%
Business, Management and Accounting 1 3%
Economics, Econometrics and Finance 1 3%
Other 1 3%
Unknown 8 28%
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 24 June 2020.
All research outputs
#7,451,584
of 22,780,967 outputs
Outputs from Mathematical Programming
#145
of 678 outputs
Outputs of similar age
#9,317
of 30,135 outputs
Outputs of similar age from Mathematical Programming
#1
of 3 outputs
Altmetric has tracked 22,780,967 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 678 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 49th percentile – i.e., 49% 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 30,135 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them