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Review on Intelligent Processing Technologies of Legal Documents

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Artificial Intelligence and Security (ICAIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13338))

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Abstract

Due to the imbalance between a large number of litigation cases and the number of judicial personnel, many legal documents to be processed greatly increase the burden of legal practitioners. So the intelligent processing of legal documents is especially important. At present, machine learning and deep learning have made great achievements in the intelligent processing of legal documents, including the elements extraction of legal documents, classification of legal documents, generation of legal documents, abstract extraction of legal documents etc. The main aim of this paper is to present a review of legal documents intelligent processing based on deep learning from legal documents representation, elements extraction of legal documents, classification of legal documents, automatic generation of legal documents.

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Author information

Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Guolong Zhao & Yuling Liu

  2. Amazon Services LLC, Seattle, USA

    E. Erdun

Authors
  1. Guolong Zhao
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  2. Yuling Liu
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  3. E. Erdun
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Corresponding author

Correspondence to Yuling Liu .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Zhao, G., Liu, Y., Erdun, E. (2022). Review on Intelligent Processing Technologies of Legal Documents. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13338. Springer, Cham. https://doi.org/10.1007/978-3-031-06794-5_55

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  • DOI: https://doi.org/10.1007/978-3-031-06794-5_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06793-8

  • Online ISBN: 978-3-031-06794-5

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