基于语义解析的KBQA论文

简单KBQA

  1. Template-based question answering over RDF data . Unger, 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 extension . Qingqing Cai, Alexander Yates . ACL(2013). [PDF]
  3. Semantic parsing on freebase from question-answer pairs . Jonathan Berant, Andrew Chou, Roy Frostig, Percy Liang . EMNLP(2013). [PDF]
  4. Large-scale semantic parsing without question-answer pairs . Siva Reddy, Mirella Lapata, Mark Steedman . TACL(2014). [PDF]
  5. Semantic parsing for single relation question answering . Wen-tau Yih, Xiaodong He, Christopher Meek . ACL(2014). [PDF]
  6. Information extraction over structured data: Question answering with Freebase . Xuchen Yao, Benjamin Van Durme . ACL(2014). [PDF]
  7. Semantic parsing via staged query graph generation: Question answering with knowledge base . Wen-tau Yih, Ming-Wei Chang, Xiaodong He, Jianfeng Gao . ACL(2015). [PDF]
  8. Simple question answering by attentive convolutional neural network . Wenpeng Yin, Mo Yu, Bing Xiang, Bowen Zhou, Hinrich Schütze . COLING(2016). [PDF]
  9. Learning to compose neural networks for question answering . Jacob 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 relations . Yunshi Lan, Shuohang Wang, Jing Jiang . TASLP(2019). [PDF]

复杂KBQA

  1. Automated template generation for question answering over knowledge graphs . Abujabal, Abdalghani, Mohamed Yahya, Mirek Riedewald, G. Weikum . WWW(2017). [PDF]
  2. Neural symbolic machines: Learning semantic parsers on Freebase with weak supervision . Chen Liang, Jonathan Berant, Quoc Le, Kenneth D. Forbus, Ni Lao . ACL(2017). [PDF ] [Code]
  3. Knowledge base question answering via encoding of complex query graphs . Kangqi Luo, Fengli Lin, Xusheng Luo, Kenny Zhu . EMNLP(2018). [PDF ] [Code]
  4. Neverending learning for open-domain question answering over knowledge bases . Abujabal, Abdalghani, Rishiraj Saha Roy, Mohamed Yahya, G. Weikum . WWW(2018). [PDF]
  5. A state-transition framework to answer complex questions over knowledge base . Sen Hu, Lei Zou, Xinbo Zhang . EMNLP(2018). [PDF]
  6. Question answering over knowledge graphs: Question understanding via template decomposition . Weiguo Zheng, Jeffrey Xu Yu, Lei Zou, Hong Cheng . VLDB(2018). [PDF]
  7. Learning to answer complex questions over knowledge bases with query composition . Bhutani, Nikita, Xinyi Zheng, H. Jagadish . CIKM(2019). [PDF]
  8. UHop: An unrestricted-hop relation extraction framework for knowledge-based question answering . Zi-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 graphs . Gaurav 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 programs . Amrita 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 Answering . Jiwei Ding, Wei Hu, Qixin Xu, Yuzhong Qu . EMNLP(2019). [PDF]
  13. Hierarchical query graph generation for complex question answering over knowledge graph . Qiu, 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 bases . Yawei 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 base . Yongrui Chen, Huiying Li, Yuncheng Hua, Guilin Qi . IJCAI(2020). [PDF ] [Code]
  16. Query graph generation for answering multi-hop complex questions from knowledge bases . Yunshi Lan, Jing Jiang . ACL(2020). [PDF ] [Code]
  17. Answering Complex Questions by Combining Information from Curated and Extracted Knowledge Bases . Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish . ACL(2020). [PDF]
  18. Leveraging abstract meaning representation for knowledge base question answering . Pavan 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
相关推荐
-Nemophilist-27 分钟前
机器学习与深度学习-1-线性回归从零开始实现
深度学习·机器学习·线性回归
成富1 小时前
文本转SQL(Text-to-SQL),场景介绍与 Spring AI 实现
数据库·人工智能·sql·spring·oracle
CSDN云计算1 小时前
如何以开源加速AI企业落地,红帽带来新解法
人工智能·开源·openshift·红帽·instructlab
艾派森1 小时前
大数据分析案例-基于随机森林算法的智能手机价格预测模型
人工智能·python·随机森林·机器学习·数据挖掘
hairenjing11231 小时前
在 Android 手机上从SD 卡恢复数据的 6 个有效应用程序
android·人工智能·windows·macos·智能手机
小蜗子2 小时前
Multi‐modal knowledge graph inference via media convergenceand logic rule
人工智能·知识图谱
SpikeKing2 小时前
LLM - 使用 LLaMA-Factory 微调大模型 环境配置与训练推理 教程 (1)
人工智能·llm·大语言模型·llama·环境配置·llamafactory·训练框架
黄焖鸡能干四碗2 小时前
信息化运维方案,实施方案,开发方案,信息中心安全运维资料(软件资料word)
大数据·人工智能·软件需求·设计规范·规格说明书
2 小时前
开源竞争-数据驱动成长-11/05-大专生的思考
人工智能·笔记·学习·算法·机器学习
ctrey_2 小时前
2024-11-4 学习人工智能的Day21 openCV(3)
人工智能·opencv·学习