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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 (61st percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
25 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 4%
Student > Ph. D. Student 1 4%
Student > Bachelor 1 4%
Researcher 1 4%
Unknown 21 84%
Readers by discipline Count As %
Computer Science 2 8%
Unspecified 1 4%
Engineering 1 4%
Unknown 21 84%
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
#8,936,408
of 26,338,415 outputs
Outputs from Journal of Computer & System Sciences
#166
of 618 outputs
Outputs of similar age
#169,054
of 490,268 outputs
Outputs of similar age from Journal of Computer & System Sciences
#2
of 4 outputs
Altmetric has tracked 26,338,415 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 618 research outputs from this source. They receive a mean Attention Score of 4.4. 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 490,268 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 61% 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.