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MRCE: A Multi-Representation Collaborative Enhancement Model for Aspect-Opinion Pair Extraction

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Neural Information Processing (ICONIP 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1794))

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Abstract

Aspect-Opinion Pair Extraction (AOPE) is an emerging combination task of fine-grained sentiment analysis. Traditional works devise pipeline frameworks for AOPE, which potentially suffer from error propagation. To solve this problem, numerous joint methods have been proposed recently. However, these joint methods have not simultaneously considered the following three points: (1) hierarchically linguistic information captured by pre-trained language models (PLMs), (2) comprehensive word-level semantic relation learning, (3) explicit and overall subtask interaction modeling. In this paper, we propose a Multi-Representation Collaborative Enhancement (MRCE) model, which can address the above three issues with a joint framework. Extensive experiments on three widely used datasets demonstrate that our model outperforms the state-of-the-art methods.

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Notes

  1. 1.

    For brevity, we refer to ATE and OTE as term extraction.

  2. 2.

    More details can be can be referred to https://github.com/guitaowufeng/LR-CNN.

  3. 3.

    https://github.com/huggingface/transformers.

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Acknowledgment

This research is supported by the National Natural Science Foundation of China under grant No. 61702500.

Author information

Authors and Affiliations

  1. School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China

    Yaxin Liu, Yan Zhou, Ziming Li & Songlin Hu

  2. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Yaxin Liu, Yan Zhou, Ziming Li, Wei Zhou & Songlin Hu

  3. HKU Business School, The University of Hong Kong, Hong Kong, China

    Dongjun Wei

Authors
  1. Yaxin Liu
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  2. Yan Zhou
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  3. Ziming Li
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  4. Dongjun Wei
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  5. Wei Zhou
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  6. Songlin Hu
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Corresponding author

Correspondence to Yan Zhou .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Indore, Indore, India

    Mohammad Tanveer

  2. Indian Institute of Information Technology - Allahabad, Prayagraj, India

    Sonali Agarwal

  3. Kobe University, Kobe, Japan

    Seiichi Ozawa

  4. Indian Institute of Technology Patna, Patna, India

    Asif Ekbal

  5. University of Innsbruck, Innsbruck, Austria

    Adam Jatowt

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Liu, Y., Zhou, Y., Li, Z., Wei, D., Zhou, W., Hu, S. (2023). MRCE: A Multi-Representation Collaborative Enhancement Model for Aspect-Opinion Pair Extraction. In: Tanveer, M., Agarwal, S., Ozawa, S., Ekbal, A., Jatowt, A. (eds) Neural Information Processing. ICONIP 2022. Communications in Computer and Information Science, vol 1794. Springer, Singapore. https://doi.org/10.1007/978-981-99-1648-1_22

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  • DOI: https://doi.org/10.1007/978-981-99-1648-1_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-1647-4

  • Online ISBN: 978-981-99-1648-1

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