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Splitting cubes: a fast and robust technique for virtual cutting

Overview of attention for article published in The Visual Computer, March 2008
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Mentioned by

video
1 YouTube creator

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
39 Mendeley
Title
Splitting cubes: a fast and robust technique for virtual cutting
Published in
The Visual Computer, March 2008
DOI 10.1007/s00371-008-0216-1
Authors

Nico Pietroni, Fabio Ganovelli, Paolo Cignoni, Roberto Scopigno

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
Switzerland 1 3%
Unknown 37 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 31%
Student > Master 6 15%
Professor 5 13%
Student > Bachelor 3 8%
Researcher 3 8%
Other 8 21%
Unknown 2 5%
Readers by discipline Count As %
Computer Science 25 64%
Engineering 10 26%
Mathematics 1 3%
Unknown 3 8%
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 08 December 2010.
All research outputs
#21,164,509
of 23,815,455 outputs
Outputs from The Visual Computer
#742
of 1,264 outputs
Outputs of similar age
#80,317
of 83,449 outputs
Outputs of similar age from The Visual Computer
#3
of 4 outputs
Altmetric has tracked 23,815,455 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,264 research outputs from this source. They receive a mean Attention Score of 2.3. This one is in the 1st percentile – i.e., 1% 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 83,449 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% 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.