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Bayesian networks for spatial learning: a workflow on using limited survey data for intelligent learning in spatial agent-based models

Overview of attention for article published in GeoInformatica, April 2019
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Mentioned by

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1 X user

Citations

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32 Dimensions

Readers on

mendeley
75 Mendeley
Title
Bayesian networks for spatial learning: a workflow on using limited survey data for intelligent learning in spatial agent-based models
Published in
GeoInformatica, April 2019
DOI 10.1007/s10707-019-00347-0
Authors

Shaheen A. Abdulkareem, Yaseen T. Mustafa, Ellen-Wien Augustijn, Tatiana Filatova

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 23%
Student > Master 9 12%
Student > Bachelor 6 8%
Lecturer 5 7%
Professor 5 7%
Other 12 16%
Unknown 21 28%
Readers by discipline Count As %
Computer Science 12 16%
Earth and Planetary Sciences 7 9%
Engineering 6 8%
Environmental Science 5 7%
Social Sciences 4 5%
Other 17 23%
Unknown 24 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 April 2019.
All research outputs
#18,679,530
of 23,144,579 outputs
Outputs from GeoInformatica
#91
of 103 outputs
Outputs of similar age
#262,976
of 349,577 outputs
Outputs of similar age from GeoInformatica
#2
of 2 outputs
Altmetric has tracked 23,144,579 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 103 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 3rd percentile – i.e., 3% 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 349,577 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.