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Timeline
X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Expressive Explanations of DNNs by Combining Concept Analysis with ILP
|
---|---|
Chapter number | 11 |
Book title |
KI 2020: Advances in Artificial Intelligence
|
Published in |
arXiv, September 2020
|
DOI | 10.1007/978-3-030-58285-2_11 |
Book ISBNs |
978-3-03-058284-5, 978-3-03-058285-2
|
Authors |
Johannes Rabold, Gesina Schwalbe, Ute Schmid, Rabold, Johannes, Schwalbe, Gesina, Schmid, Ute |
X Demographics
The data shown below were collected from the profiles of 2 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.
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 26 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 6 | 23% |
Lecturer > Senior Lecturer | 2 | 8% |
Student > Doctoral Student | 2 | 8% |
Student > Master | 2 | 8% |
Student > Bachelor | 2 | 8% |
Other | 3 | 12% |
Unknown | 9 | 35% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 8 | 31% |
Engineering | 2 | 8% |
Arts and Humanities | 1 | 4% |
Business, Management and Accounting | 1 | 4% |
Unspecified | 1 | 4% |
Other | 2 | 8% |
Unknown | 11 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 09 February 2023.
All research outputs
#6,452,593
of 23,313,051 outputs
Outputs from arXiv
#136,804
of 960,827 outputs
Outputs of similar age
#140,928
of 409,179 outputs
Outputs of similar age from arXiv
#4,475
of 33,460 outputs
Altmetric has tracked 23,313,051 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 960,827 research outputs from this source. They receive a mean Attention Score of 3.9. 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 409,179 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 65% of its contemporaries.
We're also able to compare this research output to 33,460 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.