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Mendeley readers
| Chapter title |
Machine learning for information extraction
|
|---|---|
| Chapter number | 9 |
| Book title |
Information Extraction A Multidisciplinary Approach to an Emerging Information Technology
|
| Published by |
Springer, Berlin, Heidelberg, July 1997
|
| DOI | 10.1007/3-540-63438-x_9 |
| Book ISBNs |
978-3-54-063438-6, 978-3-54-069548-6
|
| Authors |
Filippo Neri, Lorenza Saitta |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 4% |
| Japan | 2 | 4% |
| United Kingdom | 2 | 4% |
| Italy | 1 | 2% |
| Austria | 1 | 2% |
| India | 1 | 2% |
| Mexico | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 34 | 76% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 24% |
| Researcher | 9 | 20% |
| Professor > Associate Professor | 5 | 11% |
| Student > Master | 4 | 9% |
| Professor | 3 | 7% |
| Other | 10 | 22% |
| Unknown | 3 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 36 | 80% |
| Linguistics | 3 | 7% |
| Agricultural and Biological Sciences | 2 | 4% |
| Unknown | 4 | 9% |