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RETRACTED ARTICLE: The model for improving big data sub-image retrieval performance using scalable vocabulary tree based on predictive clustering

Overview of attention for article published in Cluster Computing, March 2016
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1 X user

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15 Mendeley
Title
RETRACTED ARTICLE: The model for improving big data sub-image retrieval performance using scalable vocabulary tree based on predictive clustering
Published in
Cluster Computing, March 2016
DOI 10.1007/s10586-016-0551-3
Authors

Quan-Dong Feng, Miao Xu, Xin Zhang

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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 13%
Student > Doctoral Student 2 13%
Researcher 2 13%
Student > Master 1 7%
Lecturer > Senior Lecturer 1 7%
Other 0 0%
Unknown 7 47%
Readers by discipline Count As %
Computer Science 5 33%
Business, Management and Accounting 1 7%
Social Sciences 1 7%
Unknown 8 53%
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 22 September 2018.
All research outputs
#20,533,782
of 23,103,903 outputs
Outputs from Cluster Computing
#257
of 278 outputs
Outputs of similar age
#254,503
of 300,243 outputs
Outputs of similar age from Cluster Computing
#3
of 3 outputs
Altmetric has tracked 23,103,903 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 278 research outputs from this source. They receive a mean Attention Score of 3.2. 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 300,243 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.