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A Randomized Algorithm for Online Unit Clustering

Overview of attention for article published in Theory of Computing Systems, October 2007
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About this Attention Score

  • Among the highest-scoring outputs from this source (#26 of 133)

Mentioned by

patent
1 patent

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
11 Mendeley
Title
A Randomized Algorithm for Online Unit Clustering
Published in
Theory of Computing Systems, October 2007
DOI 10.1007/s00224-007-9085-7
Authors

Timothy M. Chan, Hamid Zarrabi-Zadeh

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 45%
Student > Ph. D. Student 3 27%
Researcher 2 18%
Student > Bachelor 1 9%
Readers by discipline Count As %
Computer Science 9 82%
Economics, Econometrics and Finance 1 9%
Engineering 1 9%
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 November 2014.
All research outputs
#7,557,593
of 23,053,169 outputs
Outputs from Theory of Computing Systems
#26
of 133 outputs
Outputs of similar age
#25,606
of 72,745 outputs
Outputs of similar age from Theory of Computing Systems
#2
of 7 outputs
Altmetric has tracked 23,053,169 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 133 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 38th percentile – i.e., 38% 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 72,745 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.