Semantics-based legal citation network

  • Authors:
  • Paul Zhang;Lavanya Koppaka

  • Affiliations:
  • New Technology Research, LexisNexis, Miamisburg, OH;New Technology Research, LexisNexis, Miamisburg, OH

  • Venue:
  • Proceedings of the 11th international conference on Artificial intelligence and law
  • Year:
  • 2007

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Abstract

We describe and discuss the use of semantics-based citation networks in a new legal research tool. Such networks are generated based on citation relations between cases found in legal corpora as well as legal issues being discussed with these citations. Unlike traditional tools, the System allows legal professionals to efficiently study legal issues without having to go through whole cases or tedious manual citation search. This shift of focus from cases to individual issues within cases would greatly reduce time required for attorneys and legal scholars who have specific research problems in mind. The Systems User Interface (UI) allows users to easily navigate in the citation networks and study how citations are interrelated and how legal issues have evolved in the past. Various forms of natural language processing (NLP) technologies are used in building the metadata behind the prototype. Formal evaluation confirmed the Systems capability of accurately identifying citations relevant to given legal issues.