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Mendeley readers
Chapter title |
Improving Medical Short Text Classification with Semantic Expansion Using Word-Cluster Embedding
|
---|---|
Chapter number | 41 |
Book title |
Information Science and Applications 2018
|
Published by |
Springer, Singapore, June 2018
|
DOI | 10.1007/978-981-13-1056-0_41 |
Book ISBNs |
978-9-81-131055-3, 978-9-81-131056-0
|
Authors |
Ying Shen, Qiang Zhang, Jin Zhang, Jiyue Huang, Yuming Lu, Kai Lei, Shen, Ying, Zhang, Qiang, Zhang, Jin, Huang, Jiyue, Lu, Yuming, Lei, Kai |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 35 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 5 | 14% |
Student > Ph. D. Student | 5 | 14% |
Student > Master | 5 | 14% |
Professor > Associate Professor | 3 | 9% |
Researcher | 2 | 6% |
Other | 3 | 9% |
Unknown | 12 | 34% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 14 | 40% |
Engineering | 3 | 9% |
Biochemistry, Genetics and Molecular Biology | 2 | 6% |
Linguistics | 1 | 3% |
Mathematics | 1 | 3% |
Other | 2 | 6% |
Unknown | 12 | 34% |