Finally, we apply the proposed TJE method for NER across different domains on the ACE 2005 dataset, which is a benchmark in Natural Language Processing (NLP).

May 17, 2013 · Named Entity Recognition (NER) is a fundamental task in information extraction from unstructured text. Most previous machine-learning-based ...

Finally, we apply the proposed TJE method for NER across different domains on the ACE 2005 dataset, which is a benchmark in Natural Language Processing (NLP).

We propose a cross-task and cross-domain joint training method for multi-task ... Label embedding approach for transfer learn- · ing. In International ...

May 22, 2022 · Improving low resource named entity recognition using cross-lingual knowl- edge transfer. In Proceedings of the International. Joint ...

Abstract. Automatically tagging textual mentions with the concepts, types and entities that they represent are important tasks for which supervised learning ...

(2018) utilized the idea of transfer learning by first initializing a target model with parameters learned from source-domain NER, and then using labeled target ...

Dec 26, 2023 · Data augmentation for cross- domain named entity recognition. In ... Transfer joint embedding for cross-domain named en- tity recognition.

Experimental results on the Cross-NER benchmark show that the proposed approach has flexible transfer ability and performs better on both one-source and ...

Sep 21, 2021 · To use the embeddings, we exploit the parameter generate network (PGN) to enhance the word representations of our basic model. We apply the PGN ...