Automated Bundle Pagination Using Machine Learning

Torrisi, Alessandro, Bevan, Robert, Atkinson, Katie ORCID: 0000-0002-5683-4106, Bollegala, Danushka ORCID: 0000-0003-4476-7003 and Coenen, Frans ORCID: 0000-0003-1026-6649
(2019) Automated Bundle Pagination Using Machine Learning. In: ICAIL '19: Seventeenth International Conference on Artificial Intelligence and Law, 2019-6-17 - 2019-6-21, Montreal, Canada.

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Coherent division of legal document bundles, whether this is done in the context of court bundles, briefs or some other application, is a time consuming and challenging task. We propose an approach whereby this process can be automated. Two variations are considered. The first addresses the scenario where the topic labelling is pre-defined and adopts a supervised learning approach. The second addresses the scenario where the topic labelling, for whatever reason, is not specified in advance and adopts an unsupervised learning approach. This paper reports on an investigation of both mechanisms using accident claims bundles. The evaluation results indicate that the proposed approaches can be successfully applied to divide legal document bundles.

Item Type: Conference or Workshop Item (Unspecified)
Depositing User: Symplectic Admin
Date Deposited: 07 Jun 2019 10:49
Last Modified: 19 Jan 2023 00:43
DOI: 10.1145/3322640.3326726
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