CLMay 25, 2021

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

arXiv:2105.11644v1205 citations
Originality Synthesis-oriented
AI Analysis

It provides a comprehensive overview for researchers working on complex KBQA, but is incremental as it synthesizes existing work rather than introducing new methods.

This paper surveys methods, challenges, and solutions for complex knowledge base question answering, summarizing two mainstream approaches and reviewing advanced techniques to address typical issues in the field.

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.

Foundations

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