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Information retrieval and structural complexity of legal trees

Research output: Working paper/PreprintPreprint

Original languageEnglish
PublisherIOP Publishing Ltd.
Volume3
DOIs
Accepted/In press31 Aug 2022
Published22 Sep 2022

Publication series

NameJournal of Physics: Complexity

Bibliographical note

Funding Information: PV and ET acknowledge support from UKRI Future Leaders Fellowship scheme [n. MR/S03174X/1]. Y-PF is supported by the EPSRC Centre for Doctoral Training in Cross-disciplinary Approaches to Non-Equilibrium Systems (CANES EP/L015854/1). The authors acknowledge use of the research computing facility at King’s College London, Rosalind (https://rosalind.kcl.ac.uk). Funding Information: PV and ET acknowledge support from UKRI Future Leaders Fellowship scheme [n. MR/S03174X/1]. Y-PF is supported by the EPSRC Centre for Doctoral Training in Cross-disciplinary Approaches to Non-Equilibrium Systems (CANES EP/L015854/1). The authors acknowledge use of the research computing facility at King’s College London, Rosalind ( https://rosalind.kcl.ac.uk ). Publisher Copyright: © 2022 The Author(s). Published by IOP Publishing Ltd.

King's Authors

Abstract

We introduce a model for the retrieval of information hidden in legal texts. These are typically organised in a hierarchical (tree) structure, which a reader interested in a given provision needs to explore down to the ‘deepest’ level (articles, clauses, …). We assess the structural complexity of legal trees by computing the mean first-passage time a random reader takes to retrieve information planted in the leaves. The reader is assumed to skim through the content of a legal text based on their interests/keywords, and be drawn towards the sought information based on keywords affinity, i.e. how well the Chapters/Section headers of the hierarchy seem to match the informational content of the leaves. Using randomly generated keyword patterns, we investigate the effect of two main features of the text—the horizontal and vertical coherence—on the searching time, and consider ways to validate our results using real legal texts. We obtain numerical and analytical results, the latter based on a mean-field approximation on the level of patterns, which lead to an explicit expression for the complexity of legal trees as a function of the structural parameters of the model.

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