《Precision Event Coreference Resolution Using Neural Network Classifiers》閱讀筆記
這篇文章研究的問題是篇章內和跨篇章的事件共指消解任務。如下圖所示，本文使用的模型由簡單的兩層前饋神經網絡+softmax層組成。其輸入特徵由三部分組成： （1）event mention 1的特徵向量：embeddings of the event word，the POS tag of the event word，embedding of words in a pre-defined wind
相關文章
- 1. 《Segmentation Approach for Coreference Resolution Task》閱讀筆記
- 2. 《Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution》閱讀筆記
- 3. 《Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data》閱讀筆記
- 4. 閱讀筆記 Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data
- 5. CS224N學習筆記(十六）Coreference Resolution
- 6. 《Using recurrent neural network models for early detection of heart failure onset》閱讀筆記
- 7. 《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》閱讀筆記
- 8. 論文閱讀筆記（五十六）：Image Super-Resolution Using Deep Convolutional Networks
- 9. 論文閱讀《Edge Detection Using Convolutional Neural Network》
- 10. 閱讀筆記：Image based relighting using neural networks
- 更多相關文章...
- • RSS 閱讀器 - RSS 教程
- • C# 事件（Event） - C#教程
- • Tomcat學習筆記（史上最全tomcat學習筆記）
- • JDK13 GA發佈：5大特性解讀
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. 《Segmentation Approach for Coreference Resolution Task》閱讀筆記
- 2. 《Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution》閱讀筆記
- 3. 《Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data》閱讀筆記
- 4. 閱讀筆記 Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data
- 5. CS224N學習筆記(十六）Coreference Resolution
- 6. 《Using recurrent neural network models for early detection of heart failure onset》閱讀筆記
- 7. 《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》閱讀筆記
- 8. 論文閱讀筆記（五十六）：Image Super-Resolution Using Deep Convolutional Networks
- 9. 論文閱讀《Edge Detection Using Convolutional Neural Network》
- 10. 閱讀筆記：Image based relighting using neural networks