基于语义解析的KBQA论文

2024-02-27 02:04
文章标签 解析 论文 语义 kbqa

本文主要是介绍基于语义解析的KBQA论文,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!

简单KBQA

  1. Template-based question answering over RDF dataUnger, Christina, Lorenz Bühmann, Jens Lehmann, A. N. Ngomo, D. Gerber, P. Cimiano. WWW(2012). [PDF]
  2. Large-scale semantic parsing via schema matching and lexicon extensionQingqing Cai, Alexander Yates. ACL(2013). [PDF]
  3. Semantic parsing on freebase from question-answer pairsJonathan Berant, Andrew Chou, Roy Frostig, Percy Liang. EMNLP(2013). [PDF]
  4. Large-scale semantic parsing without question-answer pairsSiva Reddy, Mirella Lapata, Mark Steedman. TACL(2014). [PDF]
  5. Semantic parsing for single relation question answeringWen-tau Yih, Xiaodong He, Christopher Meek. ACL(2014). [PDF]
  6. Information extraction over structured data: Question answering with FreebaseXuchen Yao, Benjamin Van Durme. ACL(2014). [PDF]
  7. Semantic parsing via staged query graph generation: Question answering with knowledge baseWen-tau Yih, Ming-Wei Chang, Xiaodong He, Jianfeng Gao. ACL(2015). [PDF]
  8. Simple question answering by attentive convolutional neural networkWenpeng Yin, Mo Yu, Bing Xiang, Bowen Zhou, Hinrich Schütze. COLING(2016). [PDF]
  9. Learning to compose neural networks for question answeringJacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein. NAACL(2016). [PDF] [Code]
  10. Knowledge base question answering with a matching-aggregation model and question-specific contextual relationsYunshi Lan, Shuohang Wang, Jing Jiang. TASLP(2019). [PDF]

复杂KBQA

  1. Automated template generation for question answering over knowledge graphsAbujabal, Abdalghani, Mohamed Yahya, Mirek Riedewald, G. Weikum. WWW(2017). [PDF]
  2. Neural symbolic machines: Learning semantic parsers on Freebase with weak supervisionChen Liang, Jonathan Berant, Quoc Le, Kenneth D. Forbus, Ni Lao. ACL(2017). [PDF] [Code]
  3. Knowledge base question answering via encoding of complex query graphsKangqi Luo, Fengli Lin, Xusheng Luo, Kenny Zhu. EMNLP(2018). [PDF] [Code]
  4. Neverending learning for open-domain question answering over knowledge basesAbujabal, Abdalghani, Rishiraj Saha Roy, Mohamed Yahya, G. Weikum. WWW(2018). [PDF]
  5. A state-transition framework to answer complex questions over knowledge baseSen Hu, Lei Zou, Xinbo Zhang. EMNLP(2018). [PDF]
  6. Question answering over knowledge graphs: Question understanding via template decompositionWeiguo Zheng, Jeffrey Xu Yu, Lei Zou, Hong Cheng. VLDB(2018). [PDF]
  7. Learning to answer complex questions over knowledge bases with query compositionBhutani, Nikita, Xinyi Zheng, H. Jagadish. CIKM(2019). [PDF]
  8. UHop: An unrestricted-hop relation extraction framework for knowledge-based question answeringZi-Yuan Chen, Chih-Hung Chang, Yi-Pei Chen, Jijnasa Nayak, Lun-Wei Ku. NAACL(2019). [PDF]
  9. Multi-hop knowledge base question answering with an iterative sequence matching model. * Yunshi Lan, Shuohang Wang, Jing Jiang*. ICDM(2019). [PDF]
  10. Learning to rank query graphs for complex question answering over knowledge graphsGaurav Maheshwari, Priyansh Trivedi, Denis Lukovnikov, Nilesh Chakraborty, Asja Fischer, Jens Lehmann. ISWC(2019). [PDF] [Code]
  11. Complex program induction for querying knowledge bases in the absence of gold programsAmrita Saha, Ghulam Ahmed Ansari, Abhishek Laddha, Karthik Sankaranarayanan, Soumen Chakrabarti. TACL(2019). [PDF][Code]
  12. Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question AnsweringJiwei Ding, Wei Hu, Qixin Xu, Yuzhong Qu. EMNLP(2019). [PDF]
  13. Hierarchical query graph generation for complex question answering over knowledge graphQiu, Yunqi, K. Zhang, Yuanzhuo Wang, Xiaolong Jin, Long Bai, Saiping Guan, Xueqi Cheng. CIKM(2020). [PDF]
  14. SPARQA: skeleton-based semantic parsing for complex questions over knowledge basesYawei Sun, Lingling Zhang, Gong Cheng, Yuzhong Qu. AAAI(2020). [PDF] [Code]
  15. Formal query building with query structure prediction for complex question answering over knowledge baseYongrui Chen, Huiying Li, Yuncheng Hua, Guilin Qi. IJCAI(2020). [PDF] [Code]
  16. Query graph generation for answering multi-hop complex questions from knowledge basesYunshi Lan, Jing Jiang. ACL(2020). [PDF] [Code]
  17. Answering Complex Questions by Combining Information from Curated and Extracted Knowledge BasesNikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish. ACL(2020). [PDF]
  18. Leveraging abstract meaning representation for knowledge base question answeringPavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander Gray, Ramon Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G P Shrivatsa Bhargav, Mo Yu. Findings of ACL(2021). [PDF]
  19. Exploiting Rich Syntax for Better Knowledge Base Question Answering
  20. ​​​​​​​RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

这篇关于基于语义解析的KBQA论文的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!



http://www.chinasem.cn/article/750891

相关文章

Java图片压缩三种高效压缩方案详细解析

《Java图片压缩三种高效压缩方案详细解析》图片压缩通常涉及减少图片的尺寸缩放、调整图片的质量(针对JPEG、PNG等)、使用特定的算法来减少图片的数据量等,:本文主要介绍Java图片压缩三种高效... 目录一、基于OpenCV的智能尺寸压缩技术亮点:适用场景:二、JPEG质量参数压缩关键技术:压缩效果对比

关于WebSocket协议状态码解析

《关于WebSocket协议状态码解析》:本文主要介绍关于WebSocket协议状态码的使用方式,具有很好的参考价值,希望对大家有所帮助,如有错误或未考虑完全的地方,望不吝赐教... 目录WebSocket协议状态码解析1. 引言2. WebSocket协议状态码概述3. WebSocket协议状态码详解3

CSS Padding 和 Margin 区别全解析

《CSSPadding和Margin区别全解析》CSS中的padding和margin是两个非常基础且重要的属性,它们用于控制元素周围的空白区域,本文将详细介绍padding和... 目录css Padding 和 Margin 全解析1. Padding: 内边距2. Margin: 外边距3. Padd

Oracle数据库常见字段类型大全以及超详细解析

《Oracle数据库常见字段类型大全以及超详细解析》在Oracle数据库中查询特定表的字段个数通常需要使用SQL语句来完成,:本文主要介绍Oracle数据库常见字段类型大全以及超详细解析,文中通过... 目录前言一、字符类型(Character)1、CHAR:定长字符数据类型2、VARCHAR2:变长字符数

使用Jackson进行JSON生成与解析的新手指南

《使用Jackson进行JSON生成与解析的新手指南》这篇文章主要为大家详细介绍了如何使用Jackson进行JSON生成与解析处理,文中的示例代码讲解详细,感兴趣的小伙伴可以跟随小编一起学习一下... 目录1. 核心依赖2. 基础用法2.1 对象转 jsON(序列化)2.2 JSON 转对象(反序列化)3.

Springboot @Autowired和@Resource的区别解析

《Springboot@Autowired和@Resource的区别解析》@Resource是JDK提供的注解,只是Spring在实现上提供了这个注解的功能支持,本文给大家介绍Springboot@... 目录【一】定义【1】@Autowired【2】@Resource【二】区别【1】包含的属性不同【2】@

SpringCloud动态配置注解@RefreshScope与@Component的深度解析

《SpringCloud动态配置注解@RefreshScope与@Component的深度解析》在现代微服务架构中,动态配置管理是一个关键需求,本文将为大家介绍SpringCloud中相关的注解@Re... 目录引言1. @RefreshScope 的作用与原理1.1 什么是 @RefreshScope1.

Java并发编程必备之Synchronized关键字深入解析

《Java并发编程必备之Synchronized关键字深入解析》本文我们深入探索了Java中的Synchronized关键字,包括其互斥性和可重入性的特性,文章详细介绍了Synchronized的三种... 目录一、前言二、Synchronized关键字2.1 Synchronized的特性1. 互斥2.

Java的IO模型、Netty原理解析

《Java的IO模型、Netty原理解析》Java的I/O是以流的方式进行数据输入输出的,Java的类库涉及很多领域的IO内容:标准的输入输出,文件的操作、网络上的数据传输流、字符串流、对象流等,这篇... 目录1.什么是IO2.同步与异步、阻塞与非阻塞3.三种IO模型BIO(blocking I/O)NI

Python 中的异步与同步深度解析(实践记录)

《Python中的异步与同步深度解析(实践记录)》在Python编程世界里,异步和同步的概念是理解程序执行流程和性能优化的关键,这篇文章将带你深入了解它们的差异,以及阻塞和非阻塞的特性,同时通过实际... 目录python中的异步与同步:深度解析与实践异步与同步的定义异步同步阻塞与非阻塞的概念阻塞非阻塞同步