Concept and Context in Legal Information Retrieval

Burkhard Schafer, Tamsin Maxwell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There exist two broad approaches to information retrieval (IR) in the legal domain: those based on manual knowledge engineering (KE) and those based on natural language processing (NLP). The KE approach is grounded in artificial intelligence (AI) and case-based reasoning (CBR), whilst the NLP approach is associated with open domain statistical retrieval. We provide some original arguments regarding the focus on KE-based retrieval in the past and why this is not sustainable in the long term. Legal approaches to questioning (NLP), rather than arguing (CBR), are proposed as the appropriate jurisprudential and cognitive underpinning for legal IR. Recall within the context of precision is proposed as a better fit to law than the ‘total recall’ model of the past, wherein conceptual and contextual search are combined to improve retrieval performance for both parties in a dispute.
Original languageEnglish
Title of host publicationLegal Knowledge and Information Systems - JURIX 2008
Subtitle of host publicationThe Twenty-First Annual Conference on Legal Knowledge and Information Systems, Florence, Italy, 10-13 December 2008
EditorsEnrico Francesconi, Giovanni Sartor, Daniella Tiscornia
PublisherIOS Press
Pages63-72
Number of pages10
ISBN (Print)9781586039523, 1586039520
DOIs
Publication statusPublished - 2008

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume189

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