CANDIDATE ANSWERS FOR SPECULATIVE QUESTIONS IN A DEEP QUESTION ANSWERING SYSTEM

• 1. 一种面向全局的机器阅读理解建模中的候选答案筛选方法 [P] . 中国专利： CN108960319B . 2019.12.03
• 2. 一种面向全局的机器阅读理解建模中的候选答案筛选方法 [P] . 中国专利： CN108960319A . 2018-12-07
• 3. Candidate answers for speculative questions in a deep question answering system [P] . 美国专利： US10540411B2 . 2020-01-21

  机译： 深度问答系统中投机性问题的候选答案

• 4. CANDIDATE ANSWERS FOR SPECULATIVE QUESTIONS IN A DEEP QUESTION ANSWERING SYSTEM [P] . 美国专利： US2020019577A1 . 2020-01-16

  机译： 深层问题答疑系统中针对性问题的候选答案

• 5. Candidate answers for speculative questions in a deep question answering system [P] . 美国专利： US10467302B2 . 2019-11-05

  机译： 深度问答系统中投机性问题的候选答案

• 1. The most important questions in cancer research and clinical oncology Question 2-5. Obesity-related cancers: more questions than answers [J] . Ajit Venniyoor 癌症（英文版） . 2017,第002期
• 2. Development of a Best Answer Recommendation Model in a Community Question Answering (CQA) System [J] . Rotimi Olaosebikan, Akintoba Emmanuel Akinwonmi, Bolanle Adefowoke Ojokoh, 智能信息管理（英文） . 2021,第003期
• 3. Shallow and Deep Syntactic/Semantic Structures for Passage Reranking in Question-Answering Systems [J] . Tymoshenko Kateryna, Moschitti Alessandro ACM Transactions on Information Systems . 2019,第1期
• 4. A building regulation question answering system: A deep learning methodology [J] . Botao Zhong, Wanlei He, Ziwei Huang, Advanced engineering informatics . 2020,第Octa期
• 5. Research Progress of Automatic Question Answering System Based on Deep Learning [J] . Shiyao Zhao, Zhezhi Jin Open Access Library Journal . 2020,第6期
• 6. Deep Neural Network-Based Models for Ranking Question - Answering Pairs in Community Question Answering Systems [C] . Van-Tu Nguyen, Anh-Cuong Le International symposium on integrated uncertainty in knowledge modelling and decision making . 2018
• 7. Automatic Neural Question Generation Using Community-Based Question Answering Systems [D] . Baghaee, Tina. 2018
• 8. Question answering system using Q A site corpus Query expansion and answer candidate evaluation [O] . Kanako Komiya, Yuji Abe, Hajime Morita, -1
• 9. Incremental Improvement of a Question Answering System by Re-ranking Answer Candidates Using Machine Learning [O] . Michael Barz, Daniel Sonntag 2021

• 1. Computer English Acquisition Environment Construction Based on Question Answering Technology Based on Question Answering Technology [J] . Fei Lang1 ,Peipei Li1 ,Jian Kang2 . 国际计算机前沿大会会议论文集 . 2016,第002期
• 2. Query Expansion Based on Semantics and Statistics in Chinese Question Answering System [J] . JIA Keliang ,PANG Xiuling ,LI Zhinuo . 武汉大学自然科学学报：英文版 . 2008,第4期
• 3. A Novel Bidirectional LSTM and Attention Mechanism Based Neural Network for Answer Selection in Community Question Answering [J] . Bo Zhang ,Haowen Wang ,Longquan Jiang . 计算机、材料和连续体(英文) . 2020,第3期
• 4. 加强产教融合、校企合作,提高人才培养的针对性和适应性问题研究——基于“岗位胜任力”的高等医学教育人才培养模式研究 [C] . 孔英 ,佟春光 ,孙璐 . 辽宁省高等教育学会2016年学术年会暨第七届中青年学者论坛 . 2016
• 5. 中文问答系统中问题分类及答案候选句抽取的研究 [A] . 文勖 . 2006