| Title |
Personal research idea recommendation using research trends and a hierarchical topic model
|
|---|---|
| Published in |
Scientometrics, October 2019
|
| DOI | 10.1007/s11192-019-03258-x |
| Authors |
Hei-Chia Wang, Tzu-Ting Hsu, Yunita Sari |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 20% |
| Researcher | 4 | 16% |
| Student > Doctoral Student | 3 | 12% |
| Other | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Other | 4 | 16% |
| Unknown | 5 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 24% |
| Social Sciences | 4 | 16% |
| Business, Management and Accounting | 2 | 8% |
| Engineering | 2 | 8% |
| Economics, Econometrics and Finance | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 8 | 32% |