“概念抽取和概念关系挖掘文献讨论安排”的版本间的差异

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(建立内容为“Category:概念抽取和概念关系挖掘 文献列表详情见概念抽取和概念关系挖掘。 报告…”的新页面)
 
 
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|| 宋玉鲲  || 2021-10-17
 
|| 宋玉鲲  || 2021-10-17
 
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| 待定
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| [[:Category:Measuring prerequisite relations among concepts|Measuring prerequisite relations among concepts]]
|| 待定    || 2021-10-24  
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|| 邓招奇  || 2021-10-24  
 
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| Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions  
 
| Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions  
 
|| 骆慧颖  || 2021-10-31
 
|| 骆慧颖  || 2021-10-31
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| [[:Category:End-to-end_Named_Entity_Recognition_and_Relation_Extraction_using_Pre-trained_Language_Models|End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models]] 
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|| 焦奕霖  || 2021-11-07
 
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| Span-based Joint Entity and Relation Extraction with Transformer Pre-training   
 
| Span-based Joint Entity and Relation Extraction with Transformer Pre-training   
|| 骆慧颖  || 待定
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|| 骆慧颖  || 2021-11-28
 
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| End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models 
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| [[:DocRED:_A_Large-Scale_Document-Level_Relation_Extraction_Dataset|DocRED: A Large-Scale Document-Level Relation Extraction Dataset ]]
|| 待定  || 待定
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|| 宋玉鲲   || 2021-12-26
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| Linguistic regularities in continuous space word representations 
 
|| 待定  || 待定
 
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| Relation extraction with matrix factorization and universal schemas
 
|| 待定   || 待定
 
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| Connecting language and knowledge bases with embedding models for relation extraction
 
|| 待定  || 待定
 
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| A Review of Relational Machine Learning for Knowledge Graphs
 
|| 待定  || 待定
 
 
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2021年12月25日 (六) 22:28的最新版本


文献列表详情见概念抽取和概念关系挖掘。 报告人可以从这里选择相关文献进行分享:KRLPapers Github项目,或自行查找相关文献。

建议报告人在本站创建新的页面并写下对所分享文献的总结评述。请在创建的页面中添加两个分类:文献讨论、概念抽取和概念关系挖掘。这里是一个例子:End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models.

以下是文献讨论安排表(持续更新中):

文献篇名 报告人 日期
Translating Embeddings for Modeling Multi-relational Data 宋玉鲲 2021-10-17
Measuring prerequisite relations among concepts 邓招奇 2021-10-24
Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions 骆慧颖 2021-10-31
End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models 焦奕霖 2021-11-07
Span-based Joint Entity and Relation Extraction with Transformer Pre-training 骆慧颖 2021-11-28
DocRED: A Large-Scale Document-Level Relation Extraction Dataset 宋玉鲲 2021-12-26