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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Measuring Statistical Dependence with Hilbert-Schmidt Norms
|
|---|---|
| Chapter number | 7 |
| Book title |
Algorithmic Learning Theory
|
| Published in |
Lecture notes in computer science, October 2005
|
| DOI | 10.1007/11564089_7 |
| Book ISBNs |
978-3-54-029242-5, 978-3-54-031696-1
|
| Authors |
Gretton, Arthur, Bousquet, Olivier, Smola, Alex, Schölkopf, Bernhard, Arthur Gretton, Olivier Bousquet, Alex Smola, Bernhard Schölkopf |
| Editors |
Sanjay Jain, Hans Ulrich Simon, Etsuji Tomita |
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 542 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 2% |
| France | 4 | <1% |
| China | 3 | <1% |
| Germany | 2 | <1% |
| Japan | 2 | <1% |
| Singapore | 2 | <1% |
| Canada | 2 | <1% |
| United Kingdom | 2 | <1% |
| Hong Kong | 1 | <1% |
| Other | 7 | 1% |
| Unknown | 507 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 184 | 34% |
| Researcher | 80 | 15% |
| Student > Master | 79 | 15% |
| Student > Bachelor | 28 | 5% |
| Other | 21 | 4% |
| Other | 65 | 12% |
| Unknown | 85 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 217 | 40% |
| Engineering | 69 | 13% |
| Mathematics | 67 | 12% |
| Agricultural and Biological Sciences | 12 | 2% |
| Physics and Astronomy | 12 | 2% |
| Other | 62 | 11% |
| Unknown | 103 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 22 December 2020.
All research outputs
#7,462,560
of 22,815,414 outputs
Outputs from Lecture notes in computer science
#2,487
of 8,124 outputs
Outputs of similar age
#20,436
of 58,939 outputs
Outputs of similar age from Lecture notes in computer science
#6
of 49 outputs
Altmetric has tracked 22,815,414 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,124 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% 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 58,939 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.