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Polynomial-time equivalences and refined algorithms for longest common subsequence variants

Overview of attention for article published in Discrete Applied Mathematics, August 2024
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Title
Polynomial-time equivalences and refined algorithms for longest common subsequence variants
Published in
Discrete Applied Mathematics, August 2024
DOI 10.1016/j.dam.2024.04.006
Authors

Yuichi Asahiro, Jesper Jansson, Guohui Lin, Eiji Miyano, Hirotaka Ono, Tadatoshi Utashima

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 20 April 2024.
All research outputs
#15,775,925
of 25,756,911 outputs
Outputs from Discrete Applied Mathematics
#502
of 1,366 outputs
Outputs of similar age
#1,318
of 2,391 outputs
Outputs of similar age from Discrete Applied Mathematics
#1
of 1 outputs
Altmetric has tracked 25,756,911 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,366 research outputs from this source. They receive a mean Attention Score of 2.0. This one has gotten more attention than average, scoring higher than 62% of its peers.
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 2,391 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 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