Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
8-2021
Abstract
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.
Keywords
Knowledge representation and reasoning, General Natural language processing, General
Discipline
Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Montreal, August 19-26
First Page
4483
Last Page
4491
ISBN
9780999241196
Identifier
10.24963/ijcai.2021/611
Publisher
IJCAI
City or Country
Virtual
Citation
LAN, Yunshi; HE, Gaole; JIANG, Jinhao; JIANG, Jing; ZHAO, Wayne Xin; and WEN, Ji-Rong.
A survey on complex knowledge base question answering: Methods, challenges and solutions. (2021). Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), Montreal, August 19-26. 4483-4491.
Available at: https://ink.library.smu.edu.sg/sis_research/6762
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.24963/ijcai.2021/611