| Title |
Learning aesthetic judgements in evolutionary art systems
|
|---|---|
| Published in |
Genetic Programming and Evolvable Machines, April 2013
|
| DOI | 10.1007/s10710-013-9188-7 |
| Authors |
Yang Li, Changjun Hu, Leandro L. Minku, Haolei Zuo |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Italy | 1 | 3% |
| Austria | 1 | 3% |
| Unknown | 29 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 31% |
| Student > Master | 5 | 16% |
| Researcher | 3 | 9% |
| Student > Bachelor | 2 | 6% |
| Professor | 2 | 6% |
| Other | 4 | 13% |
| Unknown | 6 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 47% |
| Engineering | 2 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Psychology | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 9 | 28% |
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 26 February 2021.
All research outputs
#7,315,023
of 25,320,147 outputs
Outputs from Genetic Programming and Evolvable Machines
#29
of 127 outputs
Outputs of similar age
#57,092
of 203,586 outputs
Outputs of similar age from Genetic Programming and Evolvable Machines
#1
of 3 outputs
Altmetric has tracked 25,320,147 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 127 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 75% 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 203,586 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 3 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