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Automatic Query Generation from Legal Texts for Case Law Retrieval

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Information Retrieval Technology (AIRS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10648))

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Abstract

This paper investigates automatic query generation from legal decisions, along with contributing a test collection for the evaluation of case law retrieval. For a sentence or paragraph within a legal decision that cites another decision, queries were automatically generated from a proportion of the terms in that sentence or paragraph. Manually generated queries were also created as a ground to empirically compare automatic methods. Automatically generated queries were found to be more effective than the average Boolean queries from experts. However, the best keyword and Boolean queries from experts significantly outperformed automatic queries.

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Notes

  1. 1.

    The doctrine of precedent requires, broadly speaking, that like circumstances are considered in a like fashion; a case that considers a certain set of factual circumstances therefore must be followed for any future circumstances that are analogous.

  2. 2.

    The obligation of parties to litigation to disclose all documents relevant to issues between them.

  3. 3.

    A keynumber system of categorised areas and subareas of law. Areas of law can be searched or browsed by number.

  4. 4.

    Decisions were downloaded from http://courtlistener.com.

  5. 5.

    A statement by the Court as to whether it would grant review of a lower court’s decision.

  6. 6.

    https://www.elastic.co/.

  7. 7.

    \(\lambda \) is responsible for smoothing between the background language model (the legal collection), and the foreground language model (the sentence or paragraph).

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Author information

Authors and Affiliations

  1. Queensland University of Technology, Brisbane, Australia

    Daniel Locke, Guido Zuccon & Harrisen Scells

Authors
  1. Daniel Locke
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  2. Guido Zuccon
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  3. Harrisen Scells
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Corresponding author

Correspondence to Daniel Locke .

Editor information

Editors and Affiliations

  1. Korea Institute of Science and Technology Information, Daejeon, Korea (Republic of)

    Won-Kyung Sung

  2. Korea Institute of Science and Technology Information, Daejeon, Korea (Republic of)

    Hanmin Jung

  3. Beijing University of Technology, Beijing, China

    Shuo Xu

  4. Burapha University, Chonburi, Thailand

    Krisana Chinnasarn

  5. Kwansei Gakuin University, Himeji, Hyogo, Japan

    Kazutoshi Sumiya

  6. Korea Institute of Science and Technology Information, Daejeon, Korea (Republic of)

    Jeonghoon Lee

  7. Renmin University of China, Beijing, China

    Zhicheng Dou

  8. Georgetown University, Washington, District of Columbia, USA

    Grace Hui Yang

  9. Konkuk University, Seoul, Korea (Republic of)

    Young-Guk Ha

  10. Korea Institute of Science and Technology Information, Daejeon, Korea (Republic of)

    Seungbock Lee

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Locke, D., Zuccon, G., Scells, H. (2017). Automatic Query Generation from Legal Texts for Case Law Retrieval. In: Sung, WK., et al. Information Retrieval Technology. AIRS 2017. Lecture Notes in Computer Science(), vol 10648. Springer, Cham. https://doi.org/10.1007/978-3-319-70145-5_14

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  • DOI: https://doi.org/10.1007/978-3-319-70145-5_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70144-8

  • Online ISBN: 978-3-319-70145-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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