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| Chapter title |
Machine Learning Approach for IP-Flow Record Anomaly Detection
|
|---|---|
| Chapter number | 3 |
| Book title |
NETWORKING 2011
|
| Published by |
Springer, Berlin, Heidelberg, May 2011
|
| DOI | 10.1007/978-3-642-20757-0_3 |
| Book ISBNs |
978-3-64-220756-3, 978-3-64-220757-0
|
| Authors |
Cynthia Wagner, Jérôme François, Radu State, Thomas Engel |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 1% |
| Germany | 1 | 1% |
| Sweden | 1 | 1% |
| India | 1 | 1% |
| Thailand | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 61 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 27% |
| Student > Master | 15 | 22% |
| Student > Bachelor | 5 | 7% |
| Researcher | 5 | 7% |
| Student > Doctoral Student | 3 | 4% |
| Other | 7 | 10% |
| Unknown | 14 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 41 | 61% |
| Engineering | 8 | 12% |
| Agricultural and Biological Sciences | 1 | 1% |
| Mathematics | 1 | 1% |
| Unknown | 16 | 24% |