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Mendeley readers
Chapter title |
Context-Aware Data Mining vs Classical Data Mining: Case Study on Predicting Soil Moisture
|
---|---|
Chapter number | 19 |
Book title |
14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)
|
Published by |
Springer, Cham, May 2019
|
DOI | 10.1007/978-3-030-20055-8_19 |
Book ISBNs |
978-3-03-020054-1, 978-3-03-020055-8
|
Authors |
Anca Avram, Oliviu Matei, Camelia-M. Pintea, Petrica C. Pop, Carmen Ana Anton, Avram, Anca, Matei, Oliviu, Pintea, Camelia-M., Pop, Petrica C., Anton, Carmen Ana |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 16 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Lecturer | 3 | 19% |
Student > Doctoral Student | 2 | 13% |
Other | 1 | 6% |
Unspecified | 1 | 6% |
Student > Bachelor | 1 | 6% |
Other | 3 | 19% |
Unknown | 5 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 6 | 38% |
Unspecified | 1 | 6% |
Environmental Science | 1 | 6% |
Neuroscience | 1 | 6% |
Engineering | 1 | 6% |
Other | 1 | 6% |
Unknown | 5 | 31% |