Knowledge and reasoning for question answering: Research perspectives

被引:6
|
作者
Saint-Dizier, Patrick [2 ]
Moens, Marie-Francine [1 ]
机构
[1] Katholieke Univ Leuven, Dept Comp Sci, B-3001 Heverlee, Belgium
[2] CNRS, IRIT, F-31062 Toulouse, France
关键词
Question classification; Relation extraction; Discourse classification; Knowledge acquisition and reasoning;
D O I
10.1016/j.ipm.2011.04.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a roadmap of current promising research tracks in question answering with a focus on knowledge acquisition and reasoning. We show that many current techniques developed in the frame of text mining and natural language processing are ready to be integrated in question answering search systems. Their integration opens new avenues of research for factual answer finding and for advanced question answering. Advanced question answering refers to a situation where an understanding of the meaning of the question and the information source together with techniques for answer fusion and generation are needed. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:899 / 906
页数:8
相关论文
共 50 条
  • [1] Visual Question Answering Research on Joint Knowledge and Visual Information Reasoning
    Su, Zhenqiang
    Gou, Gang
    [J]. Computer Engineering and Applications, 2024, 60 (05) : 95 - 102
  • [2] Variational Reasoning for Question Answering with Knowledge Graph
    Zhang, Yuyu
    Dai, Hanjun
    Kozareva, Zornitsa
    Smola, Alexander J.
    Song, Le
    [J]. THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2018, : 6069 - 6076
  • [3] Multimodal Knowledge Reasoning for Enhanced Visual Question Answering
    Hussain, Afzaal
    Maqsood, Ifrah
    Shahzad, Muhammad
    Fraz, Muhammad Moazam
    [J]. 2022 16TH INTERNATIONAL CONFERENCE ON SIGNAL-IMAGE TECHNOLOGY & INTERNET-BASED SYSTEMS, SITIS, 2022, : 224 - 230
  • [4] Graph Reasoning Transformers for Knowledge -Aware Question Answering
    Zhao, Ruilin
    Zhao, Feng
    Hu, Liang
    Xu, Guandong
    [J]. THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 17, 2024, : 19652 - 19660
  • [5] Temporal knowledge graph question answering via subgraph reasoning
    Chen, Ziyang
    Zhao, Xiang
    Liao, Jinzhi
    Li, Xinyi
    Kanoulas, Evangelos
    [J]. KNOWLEDGE-BASED SYSTEMS, 2022, 251
  • [6] Explicit Knowledge-based Reasoning for Visual Question Answering
    Wang, Peng
    Wu, Qi
    Shen, Chunhua
    Dick, Anthony
    van den Hengel, Anton
    [J]. PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2017, : 1290 - 1296
  • [7] Joint reasoning with knowledge subgraphs for Multiple Choice Question Answering
    Zhang, Qin
    Chen, Shangsi
    Fang, Meng
    Chen, Xiaojun
    [J]. INFORMATION PROCESSING & MANAGEMENT, 2023, 60 (03)
  • [8] Multi-Hop Reasoning for Question Answering with Knowledge Graph
    Zhang, Jiayuan
    Cai, Yifei
    Zhang, Qian
    Cao, Zehao
    Cheng, Zhenrong
    Li, Dongmei
    Meng, Xianghao
    [J]. 2021 IEEE/ACIS 20TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE (ICIS 2021-SUMMER), 2021, : 121 - 125
  • [9] Structure-Aware Reasoning for Knowledge Base Question Answering
    Ma, Lu
    Zhang, Peng
    Zhu, Xi
    Luo, Dan
    Wang, Bin
    [J]. ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2022, PT I, 2022, 13280 : 562 - 573
  • [10] Research on the method of knowledge base question answering
    Jin, Tao
    Wang, Hai-Jun
    [J]. 2021 3RD INTERNATIONAL CONFERENCE ON MACHINE LEARNING, BIG DATA AND BUSINESS INTELLIGENCE (MLBDBI 2021), 2021, : 527 - 530