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Searching Case Law Judgments by Using Other Judgments as a Query

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Artificial Intelligence and Natural Language (AINL 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1292))

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Abstract

This paper presents an effective method for case law retrieval based on semantic document similarity and a web application for querying Finnish case law. The novelty of the work comes from the idea of using legal documents for automatic formulation of the query, including case law judgments, legal case descriptions, or other texts. The query documents may be in various formats, including image files with text content. This approach allows efficient search for similar documents without the need to specify a query string or keywords, which can be difficult in this use case. The application leverages two traditional word frequency based methods, TF-IDF and LDA, alongside two modern neural network methods, Doc2Vec and Doc2VecC. Effectiveness of the approach for document relevance ranking has been evaluated using a gold standard set of inter-document similarities. We show that a linear combination of similarities derived from the individual models provides a robust automatic similarity assessment for ranking the case law documents for retrieval.

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Notes

  1. 1.

    https://data.finlex.fi.

  2. 2.

    https://finto.fi/oiko/en/.

  3. 3.

    https://finto.fi/koko/en/.

  4. 4.

    http://casetext.com.

  5. 5.

    http://fastcase.com.

  6. 6.

    Cf., e.g., http://www.acclaimip.com/.

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Acknowledgements

Thanks for collaborations to Aki Hietanen, Saara Packalen, Tiina Husso, and Oili Salminen at Ministry of Justice, Finland, to Minna Tamper and Jouni Tuominen at Aalto University and University of Helsinki, and to Jari Linhala, Arttu Oksanen, and Risto Talo and at Edita Publishing Ltd. This work is part of the Anoppi project funded by Finnish Ministry of Justice (https://oikeusministerio.fi/en/project?tunnus=OM042:00/2018).

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Authors and Affiliations

  1. Semantic Computing Research Group (SeCo), Aalto University, Espoo, Finland

    Sami Sarsa & Eero Hyvönen

  2. HELDIG – Helsinki Centre for Digital Humanities, University of Helsinki, Helsinki, Finland

    Eero Hyvönen

Authors
  1. Sami Sarsa
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  2. Eero Hyvönen
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Correspondence to Sami Sarsa .

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Editors and Affiliations

  1. ITMO University, St. Petersburg, Russia

    Andrey Filchenkov

  2. Haaga-Helia University of Applied Sciences, Helsinki, Finland

    Janne Kauttonen

  3. University of Helsinki, Helsinki, Finland

    Lidia Pivovarova

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Sarsa, S., Hyvönen, E. (2020). Searching Case Law Judgments by Using Other Judgments as a Query. In: Filchenkov, A., Kauttonen, J., Pivovarova, L. (eds) Artificial Intelligence and Natural Language. AINL 2020. Communications in Computer and Information Science, vol 1292. Springer, Cham. https://doi.org/10.1007/978-3-030-59082-6_11

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  • DOI: https://doi.org/10.1007/978-3-030-59082-6_11

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