Papers by Minh Trung Nguyen
An Empirical Study on Fine-Grained Named Entity Recognition (C18-1)
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Khai Mai, Thai-Hoang Pham, Minh Trung Nguyen, Tuan Duc Nguyen, Danushka Bollegala, Ryohei Sasano, Satoshi Sekine
| Challenge: | Named entity recognition (NER) is a well studied topic in natural language processing. |
| Approach: | They propose to remove the CNN layer and use dictionary and category embeddings to improve Japanese FG-NER performance. |
| Outcome: | The proposed method improves Japanese FG-NER F-score from 66.76% to 75.18%. |
The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction (2020.findings-emnlp)
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| Challenge: | Existing methods for document-level relation extraction do not capture the representations of the nodes in the graphs. |
| Approach: | They propose to explicitly compute the representations for the nodes in the graph-based edge-oriented model for Document-level Relation Extraction (DRE) . they propose to introduce two novel representation regularization mechanisms to improve the representation vectors for DRE. |
| Outcome: | The proposed model achieves state-of-the-art performance on two benchmark datasets. |