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A Survey of Question Answering over Knowledge Base

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Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding (CCKS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1134))

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Abstract

Question Answering over Knowledge Base (KBQA) is a problem that a natural language question can be answered in knowledge bases accurately and concisely. The core task of KBQA is to understand the real semantics of a natural language question and extract it to match in the whole semantics of a knowledge base. However, it is exactly a big challenge due to variable semantics of natural language questions in a real world. Recently, there are more and more out-of-shelf approaches of KBQA in many applications. It becomes interesting to compare and analyze them so that users could choose well. In this paper, we give a survey of KBQA approaches by classifying them in two categories. Following the two categories, we introduce current mainstream techniques in KBQA, and discuss similarities and differences among them. Finally, based on this discussion, we outlook some interesting open problems.

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Acknowledgments

This work is supported by the National Key Research and Development Program of China (2017YFC0908401) and the National Natural Science Foundation of China (61672377). Xiaowang Zhang is supported by the program of Peiyang Young Scholars in Tianjin University (2019XRX-0032).

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Authors and Affiliations

  1. College of Intelligence and Computing, Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin, 300350, China

    Peiyun Wu, Xiaowang Zhang & Zhiyong Feng

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  1. Peiyun Wu
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  2. Xiaowang Zhang
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  3. Zhiyong Feng
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Corresponding authors

Correspondence to Peiyun Wu or Xiaowang Zhang .

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Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Xiaoyan Zhu

  2. Harbin Institute of Technology, Harbin, China

    Bing Qin

  3. Queen's University, Kingston, Canada

    Xiaodan Zhu

  4. Harbin Institute of Technology, Harbin, China

    Ming Liu

  5. Soochow University, Soochow, China

    Longhua Qian

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Wu, P., Zhang, X., Feng, Z. (2019). A Survey of Question Answering over Knowledge Base. In: Zhu, X., Qin, B., Zhu, X., Liu, M., Qian, L. (eds) Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding. CCKS 2019. Communications in Computer and Information Science, vol 1134. Springer, Singapore. https://doi.org/10.1007/978-981-15-1956-7_8

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  • DOI: https://doi.org/10.1007/978-981-15-1956-7_8

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