2019-EMNLP-Extractive Summarization of Long Documents by Combining Global and Local Context
摘要 提出一個針對長文檔的抽取式形成摘要的模型，將整個文檔的全局上下文和當前主題中的局部上下文結合起來。在兩個科學論文集Pubmed 和arXiv上對模型進行評估。在本文中，在決定一個句子是否是摘要的一部分時，同時捕獲全局(整個文檔)和局部上下文(例如，段落/主題)的分佈式表示。 主要貢獻有： （1）使用LSTM-minus來捕獲局部上下文向量。LSTM-minus是一種學習文本跨度的embedd
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相關文章
- 1. Global and Local Variables
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- 9. IJCAI 2018 Long-Term Human Motion Prediction by Modeling Motion Context and Enhancing Motion Dynamic
- 10. 論文筆記：Generating Wikipedia by Summarizing Long Sequences