Papers with neural semi-Markov structured support vector machine model
A Semi-Markov Structured Support Vector Machine Model for High-Precision Named Entity Recognition (P19-1)
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| Challenge: | Named entity recognition (NER) is the backbone of many NLP solutions. |
| Approach: | They propose a neural semi-Markov structured support vector machine model that controls the precision-recall trade-off by assigning weights to different types of errors in the loss-augmented inference during training. |
| Outcome: | The proposed model achieves better precision-recall trade-off at various precision levels. |