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Mendeley readers
Chapter title |
BINet: Multivariate Business Process Anomaly Detection Using Deep Learning
|
---|---|
Chapter number | 16 |
Book title |
Business Process Management
|
Published by |
Springer, Cham, August 2018
|
DOI | 10.1007/978-3-319-98648-7_16 |
Book ISBNs |
978-3-31-998647-0, 978-3-31-998648-7
|
Authors |
Timo Nolle, Alexander Seeliger, Max Mühlhäuser, Nolle, Timo, Seeliger, Alexander, Mühlhäuser, Max |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 79 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 15 | 19% |
Student > Master | 15 | 19% |
Student > Bachelor | 6 | 8% |
Researcher | 6 | 8% |
Student > Doctoral Student | 4 | 5% |
Other | 7 | 9% |
Unknown | 26 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 35 | 44% |
Engineering | 5 | 6% |
Business, Management and Accounting | 5 | 6% |
Biochemistry, Genetics and Molecular Biology | 1 | 1% |
Mathematics | 1 | 1% |
Other | 2 | 3% |
Unknown | 30 | 38% |