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Nonnegative matrix factorization and its applications in pattern recognition

Overview of attention for article published in Science Bulletin, January 2006
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Mentioned by

wikipedia
5 Wikipedia pages

Citations

dimensions_citation
84 Dimensions

Readers on

mendeley
41 Mendeley
Title
Nonnegative matrix factorization and its applications in pattern recognition
Published in
Science Bulletin, January 2006
DOI 10.1007/s11434-005-1109-6
Authors

Weixiang Liu, Nanning Zheng, Qubo You

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 2%
France 1 2%
Italy 1 2%
Germany 1 2%
Unknown 37 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 34%
Researcher 7 17%
Student > Master 6 15%
Professor > Associate Professor 4 10%
Student > Bachelor 2 5%
Other 4 10%
Unknown 4 10%
Readers by discipline Count As %
Computer Science 14 34%
Engineering 9 22%
Physics and Astronomy 4 10%
Mathematics 3 7%
Agricultural and Biological Sciences 2 5%
Other 5 12%
Unknown 4 10%
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 23 January 2023.
All research outputs
#8,535,472
of 25,374,647 outputs
Outputs from Science Bulletin
#698
of 1,744 outputs
Outputs of similar age
#45,326
of 174,005 outputs
Outputs of similar age from Science Bulletin
#1
of 11 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,744 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 35th percentile – i.e., 35% 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 174,005 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.