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Biomedical Named Entity Recognition Based on Multistage Three-Way Decisions

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Pattern Recognition (CCPR 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 663))

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Abstract

Biomedical named entity recognition (Bio-NER) is one of the most fundamental tasks in the field of biomedical information extraction. The accuracy of biomedical named entity recognition is crucial to the follow-up research work. This paper presents a method for named entity recognition based on the concept of three-way decisions. The method uses a discriminative approach named conditional random fields (CRFs) to construct models. These models follow the decision-making rule of three-way decision in all stages, the model cannot make decision arbitrarily when the information is incomplete until it gets more information. The experimental results show that our method can improve the performance for biomedical named entity recognition compared with other methods.

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Notes

  1. 1.

    http://research.nii.ac.jp/~collier/workshops/JNLPBA04st.htm.

  2. 2.

    http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA/tagger.

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Acknowledgments

The work is partially supported by the National Natural Science Foundation of China (No. 61273304, 61573259), and the program of Further Accelerating the Development of Chinese Medicine Three Year Action of Shanghai (No. ZY3-CCCX-3-6002).

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Tongji University, Shanghai, China

    Hecheng Yu, Zhihua Wei, Lijun Sun & Zhifei Zhang

  2. Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, 201804, China

    Hecheng Yu, Zhihua Wei & Lijun Sun

  3. Research Center of Big Data and Network Security, Tongji University, Shanghai, 200092, China

    Zhifei Zhang

Authors
  1. Hecheng Yu
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  2. Zhihua Wei
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  3. Lijun Sun
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  4. Zhifei Zhang
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Corresponding author

Correspondence to Zhihua Wei .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China

    Xuelong Li

  3. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Xilin Chen

  4. Tsinghua University , Beijing, China

    Jie Zhou

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  6. University of Electronic Science and Technology, Chengdu, Sichuan, China

    Hong Cheng

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© 2016 Springer Nature Singapore Pte Ltd.

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Yu, H., Wei, Z., Sun, L., Zhang, Z. (2016). Biomedical Named Entity Recognition Based on Multistage Three-Way Decisions. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 663. Springer, Singapore. https://doi.org/10.1007/978-981-10-3005-5_42

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  • DOI: https://doi.org/10.1007/978-981-10-3005-5_42

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  • Print ISBN: 978-981-10-3004-8

  • Online ISBN: 978-981-10-3005-5

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