Date: 2022
Type: Contribution to book
Modelling and explaining legal case-based reasoners through classifiers
Enrico FRANCESCONI, Georg BORGES and Christoph SORGE (eds), Legal knowledge and information systems : JURIX 2022 The thirty-fifth Annual Conference, Saarbrücken, Germany, 14-16 December 2022, Amsterdam : IOS Press, 2022, Frontiers in artificial intelligence and applications ; 362, pp. 83-92
LIU, Xinghan, LORINI, Emiliano, ROTOLO, Antonino, SARTOR, Giovanni, Modelling and explaining legal case-based reasoners through classifiers, in Enrico FRANCESCONI, Georg BORGES and Christoph SORGE (eds), Legal knowledge and information systems : JURIX 2022 The thirty-fifth Annual Conference, Saarbrücken, Germany, 14-16 December 2022, Amsterdam : IOS Press, 2022, Frontiers in artificial intelligence and applications ; 362, pp. 83-92
- https://hdl.handle.net/1814/76343
Retrieved from Cadmus, EUI Research Repository
This paper brings together factor-based models of case-based reasoning (CBR) and the logical specification of classifiers. Horty [8] has developed the factor-based models of precedent into a theory of precedential constraint. In this paper we combine binary-input classifier logic (BCL) to classifiers and their explanations given by Liu & Lorini [13, 14] with Horty’s account of factor-based CBR, since both a classifier and CBR map sets of features to decisions or classifications. We reformulate case bases in the language of BCL, and give several representation results. Furthermore, we show how notions of CBR can be analyzed by notions of classifier explanation.
Additional information:
Published: December 2022
Cadmus permanent link: https://hdl.handle.net/1814/76343
Full-text via DOI: 10.3233/FAIA220451
ISBN: 9781643683645; 9781643683652
ISSN: 0922-6389; 1879-8314
Publisher: IOS Press
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