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Comparative study between incremental and ensemble learning on data streams: Case study

Overview of attention for article published in Journal of Big Data, June 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)

Mentioned by

q&a
1 Q&A thread

Citations

dimensions_citation
51 Dimensions

Readers on

mendeley
118 Mendeley
Title
Comparative study between incremental and ensemble learning on data streams: Case study
Published in
Journal of Big Data, June 2014
DOI 10.1186/2196-1115-1-5
Authors

Wenyu Zang, Peng Zhang, Chuan Zhou, Li Guo

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Unknown 117 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 27%
Student > Master 26 22%
Researcher 9 8%
Student > Doctoral Student 9 8%
Student > Bachelor 7 6%
Other 16 14%
Unknown 19 16%
Readers by discipline Count As %
Computer Science 73 62%
Engineering 6 5%
Mathematics 3 3%
Business, Management and Accounting 3 3%
Agricultural and Biological Sciences 2 2%
Other 9 8%
Unknown 22 19%
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 01 June 2020.
All research outputs
#7,755,290
of 23,577,761 outputs
Outputs from Journal of Big Data
#135
of 356 outputs
Outputs of similar age
#74,933
of 229,808 outputs
Outputs of similar age from Journal of Big Data
#4
of 5 outputs
Altmetric has tracked 23,577,761 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 356 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has gotten more attention than average, scoring higher than 58% 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 229,808 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 54% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.