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Topic Knowledge Acquisition and Utilization for Machine Reading Comprehension in Social Media Domain

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Chinese Computational Linguistics (CCL 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12869))

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Abstract

In this paper, we focus on machine reading comprehension in social media. In this domain, one normally posts a message on the assumption that the readers have specific background knowledge. Therefore, those messages are usually short and lacking in background information, which is different from the text in the other domain. Thus, it is difficult for a machine to understand the messages comprehensively. Fortunately, a key nature of social media is clustering. A group of people tend to express their opinion or report news around one topic. Having realized this, we propose a novel method that utilizes the topic knowledge implied by the clustered messages to aid in the comprehension of those short messages. The experiments on TweetQA datasets demonstrate the effectiveness of our method.

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Notes

  1. 1.

    https://tweetqa.github.io/.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 61976211, No. 61922085, No. 61906196). This work is also supported by the Key Research Program of the Chinese Academy of Sciences (Grant NO. ZDBS-SSW-JSC006), the Open Project of Beijing Key Laboratory of Mental Disroders (2019JSJB06).

Author information

Authors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Zhixing Tian, Yuanzhe Zhang, Kang Liu & Jun Zhao

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Zhixing Tian, Kang Liu & Jun Zhao

Authors
  1. Zhixing Tian
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  2. Yuanzhe Zhang
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  3. Kang Liu
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  4. Jun Zhao
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Corresponding author

Correspondence to Zhixing Tian .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Sheng Li

  2. Tsinghua University, Beijing, China

    Maosong Sun

  3. Tsinghua University, Beijing, China

    Yang Liu

  4. Baidu (China), Beijing, China

    Hua Wu

  5. Chinese Academy of Sciences, Beijing, China

    Liu Kang

  6. Harbin Institute of Technology, Harbin, China

    Wanxiang Che

  7. Chinese Academy of Sciences, Beijing, China

    Shizhu He

  8. Beijing Language and Culture University, Beijing, China

    Gaoqi Rao

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Tian, Z., Zhang, Y., Liu, K., Zhao, J. (2021). Topic Knowledge Acquisition and Utilization for Machine Reading Comprehension in Social Media Domain. In: Li, S., et al. Chinese Computational Linguistics. CCL 2021. Lecture Notes in Computer Science(), vol 12869. Springer, Cham. https://doi.org/10.1007/978-3-030-84186-7_11

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  • DOI: https://doi.org/10.1007/978-3-030-84186-7_11

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  • Online ISBN: 978-3-030-84186-7

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