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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess
|
---|---|
Chapter number | 11 |
Book title |
Artificial Neural Networks and Machine Learning – ICANN 2016
|
Published in |
Lecture notes in computer science, August 2016
|
DOI | 10.1007/978-3-319-44781-0_11 |
Book ISBNs |
978-3-31-944780-3, 978-3-31-944781-0
|
Authors |
Omid E. David, Nathan S. Netanyahu, Lior Wolf, Eli David |
Editors |
Alessandro E.P. Villa, Paolo Masulli, Antonio Javier Pons Rivero |
X Demographics
The data shown below were collected from the profiles of 30 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 30% |
India | 3 | 10% |
Chile | 1 | 3% |
Canada | 1 | 3% |
Singapore | 1 | 3% |
Australia | 1 | 3% |
Japan | 1 | 3% |
France | 1 | 3% |
South Africa | 1 | 3% |
Other | 1 | 3% |
Unknown | 10 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 23 | 77% |
Scientists | 6 | 20% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 127 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 22 | 17% |
Student > Master | 21 | 17% |
Researcher | 19 | 15% |
Student > Bachelor | 18 | 14% |
Other | 13 | 10% |
Other | 8 | 6% |
Unknown | 26 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 64 | 50% |
Engineering | 14 | 11% |
Mathematics | 4 | 3% |
Social Sciences | 3 | 2% |
Sports and Recreations | 2 | 2% |
Other | 13 | 10% |
Unknown | 27 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 17 August 2023.
All research outputs
#2,223,962
of 25,365,817 outputs
Outputs from Lecture notes in computer science
#369
of 8,151 outputs
Outputs of similar age
#39,268
of 364,877 outputs
Outputs of similar age from Lecture notes in computer science
#18
of 464 outputs
Altmetric has tracked 25,365,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,151 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 95% 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 364,877 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 89% of its contemporaries.
We're also able to compare this research output to 464 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.