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A text mining approach to assist the general public in the retrieval of legal documents

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  • Yen‐Liang Chen
  • Yi‐Hung Liu
  • Wu‐Liang Ho

Abstract

Applying text mining techniques to legal issues has been an emerging research topic in recent years. Although some previous studies focused on assisting professionals in the retrieval of related legal documents, they did not take into account the general public and their difficulty in describing legal problems in professional legal terms. Because this problem has not been addressed by previous research, this study aims to design a text‐mining‐based method that allows the general public to use everyday vocabulary to search for and retrieve criminal judgments. The experimental results indicate that our method can help the general public, who are not familiar with professional legal terms, to acquire relevant criminal judgments more accurately and effectively.

Suggested Citation

  • Yen‐Liang Chen & Yi‐Hung Liu & Wu‐Liang Ho, 2013. "A text mining approach to assist the general public in the retrieval of legal documents," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(2), pages 280-290, February.
    • Handle: RePEc:bla:jamist:v:64:y:2013:i:2:p:280-290
    DOI: 10.1002/asi.22767
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    Cited by:

    1. I-Cheng Chang & Tai-Kuei Yu & Yu-Jie Chang & Tai-Yi Yu, 2021. "Applying Text Mining, Clustering Analysis, and Latent Dirichlet Allocation Techniques for Topic Classification of Environmental Education Journals," Sustainability, MDPI, vol. 13(19), pages 1-20, September.
    2. So-Hui Park & Dong-Gu Lee & Jin-Sung Park & Jun-Woo Kim, 2021. "A Survey of Research on Data Analytics-Based Legal Tech," Sustainability, MDPI, vol. 13(14), pages 1-24, July.

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