《A Joint Neural Model for Information Extraction with Global Features》論文筆記
2020 ACL會議《A Joint Neural Model for Information Extraction with Global Features》 論文地址 該論文提出一個名爲ONEIE的信息抽取框架，增加一個全局特徵，在實例之間和子任務之間進行聯合決策。 1. Introduction 大多數的信息抽取的聯合學習模型使用task-specific分類對獨立實體進行標記而不是使用實體
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相關文章
- 1. 論文筆記：A Neural Multi-digraph Model for Chinese NER with Gazetteers
- 2. 【論文筆記】Noise Mitigation for Neural Entity Typing and Relation Extraction
- 3. 論文札記之 - A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval...
- 4. [文獻筆記]An Unsupervised Neural Attention Model for Aspect Extraction -- Ruidan He et al.
- 5. 【論文筆記】Unsupervised Information Extraction: Regularizing Discriminative Approaches with RelDist loss
- 6. 【論文筆記】【短】Noise Mitigation for Neural Entity Typing and Relation Extraction
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- 9. Information Extraction over Structured Data: Question Answering with Freebase【論文筆記】
- 10. [EMNLP2017]End-to-End Neural Relation Extraction with Global Optimization