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A topic discovery approach for unsupervised organization of legal document collections

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Abstract

Technology has substantially transformed the way legal services operate in many different countries. With a large and complex collection of digitized legal documents, the judiciary system worldwide presents a promising scenario for the development of intelligent tools. In this work, we tackle the challenging task of organizing and summarizing the constantly growing collection of legal documents, uncovering hidden topics, or themes that later can support tasks such as legal case retrieval and legal judgment prediction. Our approach to this problem relies on topic discovery techniques combined with a variety of preprocessing techniques and learning-based vector representations of words, such as Doc2Vec and BERT-like models. The proposed method was validated using four different datasets composed of short and long legal documents in Brazilian Portuguese, from legal decisions to chapters in legal books. Analysis conducted by a team of legal specialists revealed the effectiveness of the proposed approach to uncover unique and relevant topics from large collections of legal documents, serving many purposes, such as giving support to legal case retrieval tools and also providing the team of legal specialists with a tool that can accelerate their work of labeling/tagging legal documents.

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Notes

  1. https://www.uscourts.gov/statistics-reports/federal-judicial-caseload-statistics-2021.

  2. https://www.cnj.jus.br/pesquisas-judiciarias/justica-em-numeros/.

  3. https://www.cnj.jus.br/pesquisas-judiciarias/justica-em-numeros/.

  4. https://retool.com/.

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Funding

Funding was partially provided by Jusbrasil Postdoctoral Fellowship Program, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Grant No. 001), Amazonas State Research Support Foundation - FAPEAM - through the POSGRAD project, and Conselho Nacional de Desenvolvimento Científico e Tecnológico (Grant No. 307248/2019-4).

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Author notes

  1. Edleno Silva de Moura and Altigran Soares da Silva have contributed equally to this work.

Authors and Affiliations

  1. Instituto de Computação, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil

    Daniela Vianna, Edleno Silva de Moura & Altigran Soares da Silva

  2. Jusbrasil, Salvador, Bahia, Brazil

    Edleno Silva de Moura

Authors
  1. Daniela Vianna
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  2. Edleno Silva de Moura
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  3. Altigran Soares da Silva
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Correspondence to Daniela Vianna.

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Vianna, D., de Moura, E.S. & da Silva, A.S. A topic discovery approach for unsupervised organization of legal document collections. Artif Intell Law (2023). https://doi.org/10.1007/s10506-023-09371-w

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