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Toward Subgraph-Guided Knowledge Graph Question Generation With Graph Neural Networks

Overview of attention for article published in IEEE Transactions on Neural Networks and Learning Systems, September 2024
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
78 Mendeley
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Title
Toward Subgraph-Guided Knowledge Graph Question Generation With Graph Neural Networks
Published in
IEEE Transactions on Neural Networks and Learning Systems, September 2024
DOI 10.1109/tnnls.2023.3264519
Pubmed ID
Authors

Yu Chen, Lingfei Wu, Mohammed J. Zaki

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 17%
Student > Master 11 14%
Lecturer 5 6%
Student > Postgraduate 5 6%
Researcher 5 6%
Other 10 13%
Unknown 29 37%
Readers by discipline Count As %
Computer Science 42 54%
Mathematics 1 1%
Business, Management and Accounting 1 1%
Arts and Humanities 1 1%
Economics, Econometrics and Finance 1 1%
Other 3 4%
Unknown 29 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 02 May 2023.
All research outputs
#8,349,533
of 26,588,416 outputs
Outputs from IEEE Transactions on Neural Networks and Learning Systems
#496
of 3,454 outputs
Outputs of similar age
#41,765
of 142,542 outputs
Outputs of similar age from IEEE Transactions on Neural Networks and Learning Systems
#2
of 28 outputs
Altmetric has tracked 26,588,416 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 3,454 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done well, scoring higher than 85% 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 142,542 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 70% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.