Intelligent Data Engineering and Automated Learning – IDEAL 2017
Springer, Cham
Title |
Intelligent Data Engineering and Automated Learning – IDEAL 2017
|
---|---|
Published by |
Springer, Cham, January 2017
|
DOI | 10.1007/978-3-319-68935-7 |
ISBNs |
978-3-31-968934-0, 978-3-31-968935-7
|
Editors |
Hujun Yin, Yang Gao, Songcan Chen, Yimin Wen, Guoyong Cai, Tianlong Gu, Junping Du, Antonio J. Tallón-Ballesteros, Minling Zhang |
Country | Count | As % |
---|---|---|
United States | 21 | 33% |
United Kingdom | 5 | 8% |
Germany | 3 | 5% |
Sweden | 2 | 3% |
Australia | 2 | 3% |
Canada | 2 | 3% |
Netherlands | 2 | 3% |
Denmark | 2 | 3% |
France | 1 | 2% |
Other | 2 | 3% |
Unknown | 21 | 33% |
Type | Count | As % |
---|---|---|
Scientists | 32 | 51% |
Members of the public | 29 | 46% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Country | Count | As % |
---|---|---|
Unknown | 3 | 100% |
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 2 | 67% |
Unknown | 1 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 1 | 33% |
Engineering | 1 | 33% |
Unknown | 1 | 33% |