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Mendeley readers
| Title |
Credit Analysis Using Data Mining: Application in the Case of a Credit Union
|
|---|---|
| Published by |
TECSI, August 2014
|
| DOI | 10.4301/s1807-17752014000200009 |
| Authors |
Marcos de Moraes Sousa, Reginaldo Santana Figueiredo |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 73 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 27% |
| Student > Bachelor | 11 | 15% |
| Researcher | 8 | 11% |
| Student > Doctoral Student | 6 | 8% |
| Professor | 3 | 4% |
| Other | 11 | 15% |
| Unknown | 14 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 19 | 26% |
| Business, Management and Accounting | 16 | 22% |
| Economics, Econometrics and Finance | 5 | 7% |
| Social Sciences | 4 | 5% |
| Mathematics | 3 | 4% |
| Other | 10 | 14% |
| Unknown | 16 | 22% |