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

论文出处：IJCAL 2021

作者：Yunshi Lan , Gaole He , Jinhao Jiang, Jing Jiang, Wayne Xin Zhao, Ji-Rong Wen

单位：School of Computing and Information Systems, Singapore Management University; School of Information, Renmin University of China; Beijing Key Laboratory of Big Data Management and Analysis Methods; Gaoling School of Artificial Intelligence, Renmin University of China

报告人：张芊

报告时间：2022年10月24日 下午 1:00

报告地点：贵州大学北校区博学楼624室

报告内容摘要： 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.