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A Novel Active Learning Method Using SVM for Text Classification

Overview of attention for article published in International Journal of Automation and Computing, July 2016
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Mentioned by

twitter
1 tweeter

Citations

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8 Dimensions

Readers on

mendeley
26 Mendeley
Title
A Novel Active Learning Method Using SVM for Text Classification
Published in
International Journal of Automation and Computing, July 2016
DOI 10.1007/s11633-015-0912-z
Authors

Mohamed Goudjil, Mouloud Koudil, Mouldi Bedda, Noureddine Ghoggali

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 35%
Student > Ph. D. Student 4 15%
Other 3 12%
Student > Bachelor 3 12%
Researcher 2 8%
Other 2 8%
Unknown 3 12%
Readers by discipline Count As %
Computer Science 18 69%
Engineering 4 15%
Agricultural and Biological Sciences 1 4%
Unknown 3 12%

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 20 July 2018.
All research outputs
#10,554,907
of 13,253,522 outputs
Outputs from International Journal of Automation and Computing
#68
of 201 outputs
Outputs of similar age
#199,977
of 267,931 outputs
Outputs of similar age from International Journal of Automation and Computing
#3
of 13 outputs
Altmetric has tracked 13,253,522 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 201 research outputs from this source. They receive a mean Attention Score of 1.4. This one is in the 1st percentile – i.e., 1% 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 267,931 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 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.