You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Learning local word reorderings for hierarchical phrase-based statistical machine translation
|
|---|---|
| Published in |
Machine Translation, March 2016
|
| DOI | 10.1007/s10590-016-9178-7 |
| Authors |
Jingyi Zhang, Masao Utiyama, Eiichro Sumita, Hai Zhao, Graham Neubig, Satoshi Nakamura |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| United States | 1 | 3% |
| Netherlands | 1 | 3% |
| Poland | 1 | 3% |
| Unknown | 28 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 22% |
| Lecturer | 3 | 9% |
| Student > Master | 3 | 9% |
| Student > Doctoral Student | 2 | 6% |
| Other | 2 | 6% |
| Other | 6 | 19% |
| Unknown | 9 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 44% |
| Linguistics | 5 | 16% |
| Business, Management and Accounting | 1 | 3% |
| Arts and Humanities | 1 | 3% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 9 | 28% |
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 01 March 2017.
All research outputs
#18,478,448
of 22,896,955 outputs
Outputs from Machine Translation
#101
of 129 outputs
Outputs of similar age
#218,718
of 300,300 outputs
Outputs of similar age from Machine Translation
#1
of 1 outputs
Altmetric has tracked 22,896,955 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 129 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 6th percentile – i.e., 6% 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 300,300 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 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