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Negation Scope Detection with Recurrent Neural Networks Models in Review Texts

  • Conference paper
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Social Computing (ICYCSEE 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 623))

Abstract

Identifying negation scopes in a text is an important subtask of information extraction, that can benefit other natural language processing tasks, like relation extraction, question answering and sentiment analysis. And serves the task of social media text understanding. The task of negation scope detection can be regarded as a token-level sequence labeling problem. In this paper, we propose different models based on recurrent neural networks (RNNs) and word embedding that can be successfully applied to such tasks without any task-specific feature engineering efforts. Our experimental results show that RNNs, without using any hand-crafted features, outperform feature-rich CRF-based model.

Specialized Research Fund for the Doctoral Program of Higher Education (No. 20122302110039)

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Author information

Authors and Affiliations

  1. Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology, Harbin, 150001, China

    Lydia Lazib, Yanyan Zhao, Bing Qin & Ting Liu

Authors
  1. Lydia Lazib
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  2. Yanyan Zhao
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  3. Bing Qin
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  4. Ting Liu
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Corresponding author

Correspondence to Bing Qin .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology , Harbin, China

    Wanxiang Che

  2. Harbin Engineering University , Harbin, China

    Qilong Han

  3. Harbin Institute of Technology , Harbin, China

    Hongzhi Wang

  4. Northeast Forestry University , Harbin, China

    Weipeng Jing

  5. National University of Defense Technology , Changsha, China

    Shaoliang Peng

  6. Harbin Engineering University , Harbin, China

    Junyu Lin

  7. Harbin Univ. of Science and Technology , Harbin, China

    Guanglu Sun

  8. Harbin Univ. of Science and Technology , Harbin, China

    Xianhua Song

  9. Harbin Engineering University , Harbin, China

    Hongtao Song

  10. Harbin Sea of Clouds & Computer Tech. , Harbin, China

    Zeguang Lu

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© 2016 Springer Science+Business Media Singapore

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Lazib, L., Zhao, Y., Qin, B., Liu, T. (2016). Negation Scope Detection with Recurrent Neural Networks Models in Review Texts. In: Che, W., et al. Social Computing. ICYCSEE 2016. Communications in Computer and Information Science, vol 623. Springer, Singapore. https://doi.org/10.1007/978-981-10-2053-7_44

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  • DOI: https://doi.org/10.1007/978-981-10-2053-7_44

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2052-0

  • Online ISBN: 978-981-10-2053-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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