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Succinct representation for (non)deterministic finite automata

Overview of attention for article published in Journal of Computer & System Sciences, February 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
24 Mendeley
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Title
Succinct representation for (non)deterministic finite automata
Published in
Journal of Computer & System Sciences, February 2023
DOI 10.1016/j.jcss.2022.07.002
Authors

Sankardeep Chakraborty, Roberto Grossi, Kunihiko Sadakane, Srinivasa Rao Satti

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 4%
Student > Bachelor 1 4%
Researcher 1 4%
Unknown 21 88%
Readers by discipline Count As %
Computer Science 2 8%
Engineering 1 4%
Unknown 21 88%
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 11 December 2022.
All research outputs
#8,578,315
of 25,478,886 outputs
Outputs from Journal of Computer & System Sciences
#162
of 609 outputs
Outputs of similar age
#160,736
of 473,278 outputs
Outputs of similar age from Journal of Computer & System Sciences
#2
of 4 outputs
Altmetric has tracked 25,478,886 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 609 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 28th percentile – i.e., 28% 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 473,278 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
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.