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A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data

Overview of attention for article published in ACM Transactions on Sensor Networks, November 2018
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About this Attention Score

  • Among the highest-scoring outputs from this source (#43 of 166)
  • Above-average Attention Score compared to outputs of the same age (55th percentile)

Mentioned by

wikipedia
10 Wikipedia pages

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
63 Mendeley
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Title
A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data
Published in
ACM Transactions on Sensor Networks, November 2018
DOI 10.1145/3217214
Authors

Irvan B. Arief-Ang, Margaret Hamilton, Flora D. Salim

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 17%
Student > Ph. D. Student 10 16%
Student > Bachelor 5 8%
Student > Doctoral Student 4 6%
Professor > Associate Professor 4 6%
Other 7 11%
Unknown 22 35%
Readers by discipline Count As %
Computer Science 21 33%
Engineering 9 14%
Earth and Planetary Sciences 2 3%
Energy 2 3%
Economics, Econometrics and Finance 1 2%
Other 4 6%
Unknown 24 38%
Attention Score in Context

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 29 March 2024.
All research outputs
#7,755,290
of 23,577,761 outputs
Outputs from ACM Transactions on Sensor Networks
#43
of 166 outputs
Outputs of similar age
#157,145
of 440,800 outputs
Outputs of similar age from ACM Transactions on Sensor Networks
#2
of 5 outputs
Altmetric has tracked 23,577,761 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 166 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 440,800 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 55% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.