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Asia Information Retrieval Symposium

AIRS 2019: Information Retrieval Technology pp 22–33Cite as

A Semantic Expansion-Based Joint Model for Answer Ranking in Chinese Question Answering Systems

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12004))

Abstract

Answer ranking is one of essential steps in open domain question answering systems. The ranking of the retrieved answers directly affects user satisfaction. This paper proposes a new joint model for answer ranking by leveraging context semantic features, which balances both question-answer similarities and answer ranking scores. A publicly available dataset containing 40,000 Chinese questions and 369,919 corresponding answer passages from Sogou Lab is used for experiments. Evaluation on the joint model shows a Precison@1 of 72.6%, which outperforms the state-of-the-art baseline methods.

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Notes

  1. 1.

    http://www.sogou.com/labs/.

  2. 2.

    http://radimrehurek.com/gensim/similarities/docsim.html.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (No.61772146), the OUHK 2018/19 S&T School Research Fund (R5077), and Natural Science Foundation of Guangdong Province (2018A030310051).

Author information

Authors and Affiliations

  1. Department of Linguistics and Translation, City University of Hong Kong, Hong Kong, China

    Wenxiu Xie

  2. School of Science and Technology, The Open University of Hong Kong, Hong Kong, China

    Leung-Pun Wong, Lap-Kei Lee & Oliver Au

  3. School of Computer Science, South China Normal University, Guangzhou, China

    Tianyong Hao

Authors
  1. Wenxiu Xie
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  2. Leung-Pun Wong
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  3. Lap-Kei Lee
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  4. Oliver Au
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  5. Tianyong Hao
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Corresponding author

Correspondence to Tianyong Hao .

Editor information

Editors and Affiliations

  1. Open University of Hong Kong, Hong Kong, China

    Fu Lee Wang

  2. The Education University of Hong Kong, Hong Kong, China

    Haoran Xie

  3. Chinese University of Hong Kong, Hong Kong, China

    Wai Lam

  4. Nanyang Technological University, Singapore, Singapore

    Aixin Sun

  5. Institute of Information Science, Academia Sinica, Taipei, Taiwan

    Lun-Wei Ku

  6. South China Normal University, Guangzhou, China

    Tianyong Hao

  7. Chinese Academy of Agricultural Sciences, Beijing, China

    Wei Chen

  8. Douglas College, New Westminster, BC, Canada

    Tak-Lam Wong

  9. University of Southern Queensland, Toowoomba, QLD, Australia

    Xiaohui Tao

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Cite this paper

Xie, W., Wong, LP., Lee, LK., Au, O., Hao, T. (2020). A Semantic Expansion-Based Joint Model for Answer Ranking in Chinese Question Answering Systems. In: Wang, F., et al. Information Retrieval Technology. AIRS 2019. Lecture Notes in Computer Science(), vol 12004. Springer, Cham. https://doi.org/10.1007/978-3-030-42835-8_3

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  • DOI: https://doi.org/10.1007/978-3-030-42835-8_3

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  • Online ISBN: 978-3-030-42835-8

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