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Automatic classification of provisions in legislative texts

Articolo
Data di Pubblicazione:
2007
Abstract:
Legislation usually lacks a systematic organization which makes the management and the access to norms a hard problem to face. A more analytic semantic unit of reference (provision) for legislative texts was identified. A model of provisions (provisions types and their arguments) allows to describe the semantics of rules in legislative texts. It can be used to develop advanced semantic-based applications and services on legislation. In this paper an automatic bottom-up strategy to qualify existing legislative texts in terms of provision types is described.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Model of provisions; Naïve Bayes classifier; SVM classifier; Text categorization
Elenco autori:
Francesconi, Enrico
Autori di Ateneo:
FRANCESCONI ENRICO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/76932
Pubblicato in:
ARTIFICIAL INTELLIGENCE AND LAW (DORDR., PRINT)
Journal
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URL

http://www.springerlink.com/content/7t2m520g2uw40650
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