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DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Tra
時間 2020-12-23
標籤
自然語言處理
神經網絡
pytorch
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Abstract 針對事件抽取(Event Extraction)目前面臨着訓練數據缺乏和文檔級別事件抽取兩大問題,文章開創性的提出相應的解決方案。第一,訓練數據缺乏。ACE 2005 中,各語言的文檔數不過幾百篇,對深度學習來說,這樣的數據量是不足夠的。第二,事件抽取還侷限於單個句子。而事實上,一個事件往往涉及到觸發詞和多種事件元素,觸發詞和所有的事件元素都出現在同一個句子中的理想情況並不常見,
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相關文章
1.
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction
2.
【論文翻譯】CN-DBpedia: A Never-Ending Chinese Knowledge Extraction System
3.
Automatic Parking Based on a Bird’s Eye View Vision System
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Install PWscf on a Debian or Debian based operating system
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6.
VLSI Layout Hotspot Detection Based on DiscriminativeFeature Extraction
7.
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