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A Machine-Learning-Based Data-Centric Misbehavior Detection Model for Internet of Vehicles

Overview of attention for article published in IEEE Internet of Things Journal, October 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

patent
1 patent

Readers on

mendeley
94 Mendeley
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Article details
Title
A Machine-Learning-Based Data-Centric Misbehavior Detection Model for Internet of Vehicles
Published in
IEEE Internet of Things Journal, October 2020
DOI 10.1109/jiot.2020.3035035
Authors

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Timeline Attention over time Attention Score history
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Activity
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 94 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 12 13%
Student > Doctoral Student 6 6%
Student > Bachelor 5 5%
Student > Master 5 5%
Lecturer 4 4%
Other 12 13%
Unknown 50 53%
Readers by discipline
Readers by discipline Count As %
Computer Science 27 29%
Engineering 9 10%
Business, Management and Accounting 2 2%
Energy 2 2%
Social Sciences 2 2%
Other 3 3%
Unknown 49 52%
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 26 September 2024.
All research outputs
#9,514,998
of 27,789,879 outputs
Outputs from IEEE Internet of Things Journal
#383
of 1,414 outputs
Outputs of similar age
#181,189
of 446,917 outputs
Outputs of similar age from IEEE Internet of Things Journal
#26
of 88 outputs
Altmetric has tracked 27,789,879 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,414 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 33rd percentile – i.e., 33% 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 446,917 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 53% of its contemporaries.
We're also able to compare this research output to 88 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.