2017
DOI: 10.1007/s10506-017-9216-7
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Representing dimensions within the reason model of precedent

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Cited by 25 publications
(20 citation statements)
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“…I first recall some notions concerning factors and cases often used in AI & law (e.g. by Horty (2011), Horty andBench-Capon (2012), Rigoni (2018) and Horty (2019)), although with some differences in notation. Let o and o ′ be two outcomes and Pro and Con be two disjoint sets of propositions called, respectively, the pro-and con factors, i.e., the factors favouring, respectively, outcome o and o ′ .…”
Section: Notationmentioning
confidence: 99%
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“…I first recall some notions concerning factors and cases often used in AI & law (e.g. by Horty (2011), Horty andBench-Capon (2012), Rigoni (2018) and Horty (2019)), although with some differences in notation. Let o and o ′ be two outcomes and Pro and Con be two disjoint sets of propositions called, respectively, the pro-and con factors, i.e., the factors favouring, respectively, outcome o and o ′ .…”
Section: Notationmentioning
confidence: 99%
“…Although Horty (2020) presents a revision of his reason model that does not collapse into his result model, it shares a feature with his original model (which is even more strongly present in Rigoni's 2018 model) which raises some concerns about practical applicability. For these reasons I will first formally reconstruct Rigoni's (2018) model for so-called complete dimensions and then present an alternative which, although less expressive than Horty's and Rigoni's reaosn models, is arguably easier to apply in practice.…”
Section: Adapting the Approach To Dimensionsmentioning
confidence: 99%
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“…As discussed in[20], several of the systems use dimensions, which have magnitudes and range from an extreme pro-plaintiff point to an extreme pro-defendant point, rather than factors. For simplicity we will just use factors (which can be regarded as particular points or ranges on a dimension[101]).…”
mentioning
confidence: 99%