| Title |
Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm
|
|---|---|
| Published in |
Mathematical Programming Computation, July 2012
|
| DOI | 10.1007/s12532-012-0044-1 |
| Authors |
Zaiwen Wen, Wotao Yin, Yin Zhang |
Mendeley readers
The data shown below were compiled from readership statistics for 179 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 4% |
| China | 2 | 1% |
| Belgium | 1 | <1% |
| Japan | 1 | <1% |
| France | 1 | <1% |
| Unknown | 166 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 71 | 40% |
| Student > Master | 17 | 9% |
| Researcher | 14 | 8% |
| Student > Bachelor | 14 | 8% |
| Professor | 8 | 4% |
| Other | 29 | 16% |
| Unknown | 26 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 55 | 31% |
| Engineering | 44 | 25% |
| Mathematics | 30 | 17% |
| Physics and Astronomy | 4 | 2% |
| Social Sciences | 3 | 2% |
| Other | 9 | 5% |
| Unknown | 34 | 19% |
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 30 June 2017.
All research outputs
#7,552,525
of 23,039,416 outputs
Outputs from Mathematical Programming Computation
#24
of 84 outputs
Outputs of similar age
#55,341
of 165,385 outputs
Outputs of similar age from Mathematical Programming Computation
#1
of 3 outputs
Altmetric has tracked 23,039,416 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 84 research outputs from this source. They receive a mean Attention Score of 3.3. This one has gotten more attention than average, scoring higher than 54% 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 165,385 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% 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. This one has scored higher than all of them