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Context pre-modeling: an empirical analysis for classification based user-centric context-aware predictive modeling

Overview of attention for article published in Journal of Big Data, July 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
55 Mendeley
Title
Context pre-modeling: an empirical analysis for classification based user-centric context-aware predictive modeling
Published in
Journal of Big Data, July 2020
DOI 10.1186/s40537-020-00328-3
Authors

Iqbal H. Sarker, Hamed Alqahtani, Fawaz Alsolami, Asif Irshad Khan, Yoosef B. Abushark, Mohammad Khubeb Siddiqui

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 13%
Student > Master 7 13%
Researcher 5 9%
Lecturer 4 7%
Student > Doctoral Student 3 5%
Other 6 11%
Unknown 23 42%
Readers by discipline Count As %
Computer Science 12 22%
Engineering 9 16%
Social Sciences 2 4%
Business, Management and Accounting 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 6 11%
Unknown 23 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 31 March 2022.
All research outputs
#6,639,784
of 23,460,553 outputs
Outputs from Journal of Big Data
#113
of 354 outputs
Outputs of similar age
#143,833
of 400,807 outputs
Outputs of similar age from Journal of Big Data
#9
of 22 outputs
Altmetric has tracked 23,460,553 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 354 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one has gotten more attention than average, scoring higher than 66% 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 400,807 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 63% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.