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Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
時間 2020-12-30
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relation extraction
PCNN
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主要貢獻 提出使用PCNN來自動提取特徵。 往PCNN中加入multi-instance learning,用來解決遠程監督引發的錯誤標籤問題。 提出分段進行max pooling,從而考慮兩個Entity之間的結構特徵。 作者提出,之前關於關係分類的方法主要分爲2種: 1. 基於特徵的方法,這種方式對人工特徵向量的要求較高,需要爲數據集找出一種合適的特徵表示。 2. 基於kernel的方法,這種
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相關文章
1.
Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
2.
[論文研讀]Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
3.
[EMNLP2015]Distant supervision for Relation Extraction via Piecewise Convolutional Neural Networks
4.
論文筆記:Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
5.
NLP——Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
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【論文閱讀筆記PCNN】Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
7.
nlp論文學習(關係抽取)——Distant Supervision for Relation Extraction via Piecewise Convolutional Neural (2015)
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【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
9.
《GAN Driven Semi-distant Supervision for Relation Extraction》解讀
10.
論文淺嘗 | Distant Supervision for Relation Extraction
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