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On the use of fuzzy inference techniques in assessment models: part II: industrial applications

Overview of attention for article published in Fuzzy Optimization and Decision Making, June 2008
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Mentioned by

wikipedia
2 Wikipedia pages

Readers on

mendeley
30 Mendeley
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Title
On the use of fuzzy inference techniques in assessment models: part II: industrial applications
Published in
Fuzzy Optimization and Decision Making, June 2008
DOI 10.1007/s10700-008-9037-y
Authors

Kai Meng Tay, Chee Peng Lim

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 3%
Japan 1 3%
Poland 1 3%
Australia 1 3%
Unknown 26 87%

Demographic breakdown

Readers by professional status Count As %
Other 4 13%
Student > Master 4 13%
Professor 2 7%
Student > Bachelor 2 7%
Lecturer > Senior Lecturer 2 7%
Other 6 20%
Unknown 10 33%
Readers by discipline Count As %
Engineering 10 33%
Computer Science 3 10%
Mathematics 1 3%
Business, Management and Accounting 1 3%
Decision Sciences 1 3%
Other 1 3%
Unknown 13 43%
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 07 November 2019.
All research outputs
#7,917,073
of 23,857,313 outputs
Outputs from Fuzzy Optimization and Decision Making
#2
of 13 outputs
Outputs of similar age
#29,573
of 83,961 outputs
Outputs of similar age from Fuzzy Optimization and Decision Making
#1
of 2 outputs
Altmetric has tracked 23,857,313 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 13 research outputs from this source. They receive a mean Attention Score of 2.3. This one scored the same or higher as 11 of them.
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 83,961 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% 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. This one has scored higher than all of them