↓ Skip to main content

Extracting alternative machining features: An algorithmic approach

Overview of attention for article published in Research in Engineering Design, September 1995
Altmetric Badge

About this Attention Score

  • Among the highest-scoring outputs from this source (#16 of 104)

Mentioned by

patent
1 patent

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
26 Mendeley
Title
Extracting alternative machining features: An algorithmic approach
Published in
Research in Engineering Design, September 1995
DOI 10.1007/bf01638098
Authors

William C. Regli, Satyandra K. Gupta, Dana S. Nau

Mendeley readers

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 %
United States 2 8%
Colombia 1 4%
France 1 4%
Unknown 22 85%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Student > Ph. D. Student 6 23%
Professor 3 12%
Lecturer 2 8%
Student > Doctoral Student 2 8%
Other 4 15%
Unknown 3 12%
Readers by discipline Count As %
Engineering 14 54%
Business, Management and Accounting 1 4%
Agricultural and Biological Sciences 1 4%
Computer Science 1 4%
Mathematics 1 4%
Other 4 15%
Unknown 4 15%
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 17 March 2016.
All research outputs
#7,557,888
of 23,054,359 outputs
Outputs from Research in Engineering Design
#16
of 104 outputs
Outputs of similar age
#7,098
of 24,076 outputs
Outputs of similar age from Research in Engineering Design
#1
of 2 outputs
Altmetric has tracked 23,054,359 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 104 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 33rd percentile – i.e., 33% 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 24,076 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% 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