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A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions

  • Yunshi Lan
  • , Gaole He
  • , Jinhao Jiang
  • , Jing Jiang
  • , Wayne Xin Zhao*
  • , Ji Rong Wen
  • *此作品的通讯作者
  • Singapore Management University
  • School of Information
  • Beijing Key Laboratory of Big Data Management and Analysis Methods
  • Gaoling School of Artificial Intelligence

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Recently, a large number of studies focus on semantically or syntactically complicated questions. In this paper, we elaborately summarize the typical challenges and solutions for complex KBQA. We begin with introducing the background about the KBQA task. Next, we present the two mainstream categories of methods for complex KBQA, namely semantic parsing-based (SP-based) methods and information retrieval-based (IR-based) methods. We then review the advanced methods comprehensively from the perspective of the two categories. Specifically, we explicate their solutions to the typical challenges. Finally, we conclude and discuss some promising directions for future research.

源语言英语
主期刊名Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
编辑Zhi-Hua Zhou
出版商International Joint Conferences on Artificial Intelligence
4483-4491
页数9
ISBN(电子版)9780999241196
DOI
出版状态已出版 - 2021
已对外发布
活动30th International Joint Conference on Artificial Intelligence, IJCAI 2021 - Virtual, Online, 加拿大
期限: 19 8月 202127 8月 2021

出版系列

姓名IJCAI International Joint Conference on Artificial Intelligence
ISSN(印刷版)1045-0823

会议

会议30th International Joint Conference on Artificial Intelligence, IJCAI 2021
国家/地区加拿大
Virtual, Online
时期19/08/2127/08/21

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