JavaShuo
欄目
標籤
Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions
時間 2020-12-30
標籤
sentence-level Attention
简体版
原文
原文鏈接
主要貢獻 作者提出了基於句子級別的Attention模型來選擇有效的句子。 從FreeBase和Wikipedia頁面去獲取實體描述,從而彌補背景知識不足的缺陷,從而給實體更好的representation。 做了很多實驗,效果很好。 任務定義 所有句子被分到N組bags中, {B1,B2,⋯,Bi} { B 1 , B 2 , ⋯ , B i } 每個bag中的的句子都描述了同一組實
>>阅读原文<<
相關文章
1.
【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
2.
論文淺嘗 | Distant Supervision for Relation Extraction
3.
Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
4.
《GAN Driven Semi-distant Supervision for Relation Extraction》解讀
5.
論文解讀:Combining Distant and Direct Supervision for Neural Relation Extraction
6.
《Neural Relation Extraction with Selective Attention over Instances》淺析
7.
[ACL2016]Neural Relation Extraction with Selective Attention over Instances
8.
論文筆記8:Distant Supervision for Relation Extraction beyond the Sentence Boundary
9.
Distant supervision for relation extraction without labeled data論文理解
10.
[論文研讀]Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
更多相關文章...
•
Swift for 循環
-
Swift 教程
•
Scala for循環
-
Scala教程
•
RxJava操作符(七)Conditional and Boolean
•
算法總結-股票買賣
相關標籤/搜索
extraction
supervision
relation
descriptions
distant
attention
entity
win8.1+entity
action.....and
linq&entity
0
分享到微博
分享到微信
分享到QQ
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。
最新文章
1.
python的安裝和Hello,World編寫
2.
重磅解讀:K8s Cluster Autoscaler模塊及對應華爲雲插件Deep Dive
3.
鴻蒙學習筆記2(永不斷更)
4.
static關鍵字 和構造代碼塊
5.
JVM筆記
6.
無法啓動 C/C++ 語言服務器。IntelliSense 功能將被禁用。錯誤: Missing binary at c:\Users\MSI-NB\.vscode\extensions\ms-vsc
7.
【Hive】Hive返回碼狀態含義
8.
Java樹形結構遞歸(以時間換空間)和非遞歸(以空間換時間)
9.
數據預處理---缺失值
10.
都要2021年了,現代C++有什麼值得我們學習的?
本站公眾號
歡迎關注本站公眾號,獲取更多信息
相關文章
1.
【Part two: Related Work】Relation Extraction with Distant Supervision(DS)
2.
論文淺嘗 | Distant Supervision for Relation Extraction
3.
Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
4.
《GAN Driven Semi-distant Supervision for Relation Extraction》解讀
5.
論文解讀:Combining Distant and Direct Supervision for Neural Relation Extraction
6.
《Neural Relation Extraction with Selective Attention over Instances》淺析
7.
[ACL2016]Neural Relation Extraction with Selective Attention over Instances
8.
論文筆記8:Distant Supervision for Relation Extraction beyond the Sentence Boundary
9.
Distant supervision for relation extraction without labeled data論文理解
10.
[論文研讀]Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks
>>更多相關文章<<