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A Semantic Query Engine for Knowledge Rich Legal Digital Libraries

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Information Management and Big Data (SIMBig 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1837))

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Abstract

Contemporary legal digital libraries such as Lexis Nexis and WestLaw allow users to search case laws using sophisticated search tools. The sophistication of these legal search tools, however, vary widely between commercial and non-commercial libraries, and by user groups. At its core, various forms of keyword search and indexing are used to find documents of interest. While newer search engines leveraging semantic technologies such as knowledgebases, natural language processing, and knowledge graphs are becoming available, legal databases are yet to take advantage of them fully. Even more scarce is any search engine able to support reasoning to identify legal documents based on legal precedent matching. In this paper, we introduce an experimental legal document search engine, called Prism, that is capable of supporting legal argument based search to support legal claims. We use a document engineering method to embed legal premise graphs, called the AND-OR graph, in the document to facilitate semantic match. A prototype implementation of Prism as a component of a document management system, called VOiC, is also discussed.

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Notes

  1. 1.

    http://www.courts.state.va.us/opinions/opncavwp/2654044.pdf.

  2. 2.

    http://touchngo.com/sp/html/sp-4293.htm.

  3. 3.

    http://www.courts.state.va.us/opinions/opncavwp/2510061.pdf.

  4. 4.

    http://www.courts.state.va.us/opinions/opncavwp/1079041.pdf.

  5. 5.

    https://www.michbar.org/opinions/appeals/2007/081407/36789.pdf.

  6. 6.

    http://www.michbar.org/opinions/appeals/2005/030105/26467.pdf.

  7. 7.

    jurisdiction/4 means the predicate jurisdiction has four arguments.

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Acknowledgement

This publication was partially made possible by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant #P20GM103408. We acknowledge that Hayden Carroll, Austin Kugler, and Kallol Naha helped build parts of first edition of the VOiC and the Prism systems as a class research project.

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Authors and Affiliations

  1. Department of Computer Science, University of Idaho, Moscow, ID, USA

    Hasan M. Jamil

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  1. Hasan M. Jamil
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Correspondence to Hasan M. Jamil .

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Editors and Affiliations

  1. National Institutes of Health, Bethesda, MD, USA

    Juan Antonio Lossio-Ventura

  2. Visibilia, Sao Carlos, Brazil

    Jorge Valverde-Rebaza

  3. Peruvian University of Applied Sciences, Lima, Peru

    Eduardo Díaz

  4. Pontifical Catholic University of Peru, Lima, Peru

    Hugo Alatrista-Salas

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Jamil, H.M. (2023). A Semantic Query Engine for Knowledge Rich Legal Digital Libraries. In: Lossio-Ventura, J.A., Valverde-Rebaza, J., Díaz, E., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2022. Communications in Computer and Information Science, vol 1837. Springer, Cham. https://doi.org/10.1007/978-3-031-35445-8_4

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  • DOI: https://doi.org/10.1007/978-3-031-35445-8_4

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