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Learning States and Rules for Detecting Anomalies in Time Series

Overview of attention for article published in Applied Intelligence, December 2005
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#27 of 1,684)
  • High Attention Score compared to outputs of the same age (81st percentile)

Mentioned by

policy
1 policy source
patent
1 patent

Citations

dimensions_citation
87 Dimensions

Readers on

mendeley
118 Mendeley
citeulike
3 CiteULike
Title
Learning States and Rules for Detecting Anomalies in Time Series
Published in
Applied Intelligence, December 2005
DOI 10.1007/s10489-005-4610-3
Authors

Stan Salvador, Philip Chan

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Russia 1 <1%
Germany 1 <1%
Unknown 115 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 30%
Student > Master 21 18%
Student > Bachelor 13 11%
Researcher 9 8%
Student > Doctoral Student 5 4%
Other 14 12%
Unknown 21 18%
Readers by discipline Count As %
Computer Science 59 50%
Engineering 18 15%
Mathematics 4 3%
Business, Management and Accounting 2 2%
Physics and Astronomy 2 2%
Other 8 7%
Unknown 25 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 06 August 2019.
All research outputs
#4,736,890
of 22,953,506 outputs
Outputs from Applied Intelligence
#27
of 1,684 outputs
Outputs of similar age
#18,620
of 147,222 outputs
Outputs of similar age from Applied Intelligence
#1
of 1 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,684 research outputs from this source. They receive a mean Attention Score of 1.0. This one has done particularly well, scoring higher than 97% 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 147,222 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 81% of its contemporaries.
We're also able to compare this research output to 1 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