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Neural machine translation for low-resource languages without parallel corpora

Overview of attention for article published in Machine Translation, November 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#17 of 144)
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

policy
1 policy source
twitter
4 X users
patent
1 patent

Citations

dimensions_citation
50 Dimensions

Readers on

mendeley
104 Mendeley
Title
Neural machine translation for low-resource languages without parallel corpora
Published in
Machine Translation, November 2017
DOI 10.1007/s10590-017-9203-5
Authors

Alina Karakanta, Jon Dehdari, Josef van Genabith

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 18%
Student > Master 16 15%
Student > Doctoral Student 7 7%
Other 6 6%
Student > Bachelor 5 5%
Other 19 18%
Unknown 32 31%
Readers by discipline Count As %
Computer Science 50 48%
Linguistics 9 9%
Arts and Humanities 2 2%
Unspecified 2 2%
Engineering 2 2%
Other 5 5%
Unknown 34 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 30 March 2023.
All research outputs
#4,280,834
of 26,017,215 outputs
Outputs from Machine Translation
#17
of 144 outputs
Outputs of similar age
#71,813
of 347,268 outputs
Outputs of similar age from Machine Translation
#1
of 9 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 144 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 88% 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 347,268 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 9 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