Name
Abstract | ||
|---|---|---|
•Novel models are proposed for recognizing discontinuous and overlapped entities.•The models are based on bidirectional LSTMs and CRFs.•The models require little feature engineering.•Results are competitive compared with state-of-the-art systems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patrec.2017.06.009 | Pattern Recognition Letters |
Keywords | Field | DocType |
Biomedical entity recognition,Irregular entity,LSTM,CRF | Conditional random field,Data mining,Pattern recognition,Computer science,Biomedical text mining,Feature engineering,Artificial intelligence,Artificial neural network,Named-entity recognition,Machine learning,Deep neural networks,CRFS | Journal |
Volume | ISSN | Citations |
105 | 0167-8655 | 3 |
PageRank | References | Authors |
0.39 | 26 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fei Li | 1 | 6 | 2.90 |
| Meishan Zhang | 2 | 221 | 20.36 |
| Bo Tian | 3 | 3 | 0.39 |
| Bo Chen | 4 | 7 | 1.73 |
| Guohong Fu | 5 | 192 | 28.22 |
| Donghong Ji | 6 | 892 | 120.08 |