| Title |
Data mining approach for predicting the daily Internet data traffic of a smart university
|
|---|---|
| Published in |
Journal of Big Data, February 2019
|
| DOI | 10.1186/s40537-019-0176-5 |
| Authors |
Aderibigbe Israel Adekitan, Jeremiah Abolade, Olamilekan Shobayo |
Mendeley readers
The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 92 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 23% |
| Lecturer | 15 | 16% |
| Student > Bachelor | 7 | 8% |
| Student > Ph. D. Student | 6 | 7% |
| Student > Doctoral Student | 6 | 7% |
| Other | 17 | 18% |
| Unknown | 20 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 29% |
| Engineering | 18 | 20% |
| Business, Management and Accounting | 10 | 11% |
| Social Sciences | 3 | 3% |
| Arts and Humanities | 2 | 2% |
| Other | 10 | 11% |
| Unknown | 22 | 24% |