This article continues the research initiated in [1,2], which established a connection between Boolean classifiers and legal case-based reasoning. We relax the assumption that case bases are such that all situations have been decided in favour of the defendant or the plaintiff and we introduce an inductive strategy for assigning plausible outcomes to undecided cases. Using counterfactual reasoning, we propose a method to determine whether, at each step of the induction, a feature is a factor, i.e., it consistently favours a single outcome, or is irrelevant, i.e., it is does not favour any outcome, or is ambiguous, i.e., it favours opposite outcomes.

Inferring New Classifications in Legal Case-Based Reasoning / Di Florio, Cecilia; Liu, Xinghan; Lorini, Emiliano; Rotolo, Antonino; Sartor, Giovanni. - STAMPA. - 379:(2023), pp. 23-32. [10.3233/faia230942]

Inferring New Classifications in Legal Case-Based Reasoning

Di Florio, Cecilia
;
Rotolo, Antonino
;
Sartor, Giovanni
2023

Abstract

This article continues the research initiated in [1,2], which established a connection between Boolean classifiers and legal case-based reasoning. We relax the assumption that case bases are such that all situations have been decided in favour of the defendant or the plaintiff and we introduce an inductive strategy for assigning plausible outcomes to undecided cases. Using counterfactual reasoning, we propose a method to determine whether, at each step of the induction, a feature is a factor, i.e., it consistently favours a single outcome, or is irrelevant, i.e., it is does not favour any outcome, or is ambiguous, i.e., it favours opposite outcomes.
2023
Legal Knowledge and Information Systems (JURIX 2023)
23
32
Inferring New Classifications in Legal Case-Based Reasoning / Di Florio, Cecilia; Liu, Xinghan; Lorini, Emiliano; Rotolo, Antonino; Sartor, Giovanni. - STAMPA. - 379:(2023), pp. 23-32. [10.3233/faia230942]
Di Florio, Cecilia; Liu, Xinghan; Lorini, Emiliano; Rotolo, Antonino; Sartor, Giovanni
File in questo prodotto:
File Dimensione Formato  
Inferring New Classifications in Legal Case-Based Reasoning.pdf

accesso aperto

Tipo: Versione (PDF) editoriale
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale (CCBYNC)
Dimensione 289.87 kB
Formato Adobe PDF
289.87 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/961676
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact