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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
LSTM-Based Anomaly Detection: Detection Rules from Extreme Value Theory
|
---|---|
Chapter number | 48 |
Book title |
Progress in Artificial Intelligence
|
Published in |
arXiv, August 2019
|
DOI | 10.1007/978-3-030-30241-2_48 |
Book ISBNs |
978-3-03-030240-5, 978-3-03-030241-2
|
Authors |
Neema Davis, Gaurav Raina, Krishna Jagannathan, Davis, Neema, Raina, Gaurav, Jagannathan, Krishna |
X Demographics
The data shown below were collected from the profiles of 14 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 | 2 | 14% |
Australia | 2 | 14% |
Serbia | 1 | 7% |
Indonesia | 1 | 7% |
Unknown | 8 | 57% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 86% |
Scientists | 2 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 22 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 23% |
Researcher | 3 | 14% |
Other | 2 | 9% |
Student > Master | 2 | 9% |
Student > Doctoral Student | 1 | 5% |
Other | 2 | 9% |
Unknown | 7 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 45% |
Nursing and Health Professions | 1 | 5% |
Environmental Science | 1 | 5% |
Neuroscience | 1 | 5% |
Engineering | 1 | 5% |
Other | 0 | 0% |
Unknown | 8 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 18 September 2019.
All research outputs
#5,281,053
of 24,980,180 outputs
Outputs from arXiv
#112,098
of 1,018,032 outputs
Outputs of similar age
#95,520
of 345,881 outputs
Outputs of similar age from arXiv
#3,431
of 26,377 outputs
Altmetric has tracked 24,980,180 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,018,032 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 88% 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 345,881 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 72% of its contemporaries.
We're also able to compare this research output to 26,377 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.