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Mendeley readers
Attention Score in Context
| Title |
The method to divide a sentence of requirement into individual requirements and the development of requirement specification editor which can describe individual requirements
|
|---|---|
| Published in |
SpringerPlus, April 2013
|
| DOI | 10.1186/2193-1801-2-145 |
| Pubmed ID | |
| Authors |
Kuniya Sato, Masahiro Ooba, Tomohiko Takagi, Zengo Furukawa, Seiichi Komiya, Rihito Yaegashi |
| Abstract |
Agile software development gains requirements from the direct discussion with customers and the development staff each time, and the customers evaluate the appropriateness of the requirement. If the customers divide the complicated requirement into individual requirements, the engineer who is in charge of software development can understand it easily. This is called division of requirement. However, the customers do not understand how much and how to divide the requirements. |
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 % |
|---|---|---|
| Japan | 1 | 7% |
| Unknown | 14 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 27% |
| Student > Ph. D. Student | 3 | 20% |
| Student > Bachelor | 2 | 13% |
| Lecturer | 2 | 13% |
| Student > Doctoral Student | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 67% |
| Engineering | 2 | 13% |
| Social Sciences | 1 | 7% |
| Unknown | 2 | 13% |
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 05 April 2013.
All research outputs
#20,187,333
of 22,703,044 outputs
Outputs from SpringerPlus
#1,461
of 1,852 outputs
Outputs of similar age
#174,519
of 199,925 outputs
Outputs of similar age from SpringerPlus
#72
of 135 outputs
Altmetric has tracked 22,703,044 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 1,852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. 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 199,925 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 135 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.