Abstract
In the last few years bureaucratic procedures didn’t show a significant reduction in the volume of paper documents created. In order to reduce the huge amount of space for archiving and preserving documents and to speed up the secarh process, a semantic-based dematerialization process should be performed. In this paper we describe a novel system that manages several kind of bureaucratic documents in the e-gov domain, automatically extracts several interesting information and produces a suitable semantic representation that may be considered as the first step towards a full automated document management system.
Chapter PDF
Similar content being viewed by others
Keywords
- Knowledge Representation
- Natural Language Processing
- Resource Description Framework
- Text Segmentation
- Government Document
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Valente, A., Breuker, J.: A functional ontology of law (1994)
Visser, P.: The formal specification of a legal ontology (1996)
McCarty, L.T.: A language for legal discourse i. basic features. In: ICAIL ’89: Proceedings of the 2nd international conference on Artificial intelligence and law, New York, NY, USA, ACM (1989) 180–189
Stamper, R.: The role of semantics in legal expert systems and legal reasoning. Ratio Juris 4(2) (1991) 219–244
Tiscornia, D.: Some ontological tools to support legal regulatory compliance, with a case study. Workshop on Regulatory Ontologies and the Modeling of Complaint Regulations (WORM CoRe 2003) Springer LNCS (November 2003)
Jacobs P S, R.L.F.: Scisor: Extracting information from on-line news. Comm ACM 33(11) (1990) 88–97
et al, H.J.R.: Sri international: Description of the fastus system used for muc-4. Fourth Message Understanding Conference, Morgan Kaufmann (1992) 143–147
et all, M.S.: A full-text retrieval system with a dynamic abstract generation function. in Proc SIGIR 94 (1994) 152–161
Bruninghaus St, A.K.D.: Finding factors: Learning to classify case opinions under abstract fact categories. in Proc ICAIL’97 (1997) 123–131
Zanchetta, E., Baroni, M.: Morph-it! a free corpus-based morphological resource for the italian language. Proceedings of Corpus Linguistics 2005 (2005) 23–32
Roventini, A.: Italwordnet: Building a large semantic database for the automatic treatment of the italian language. In Zampolli, A., Calzolari, N., Cignoni, L. (eds.), Computational Linguistics in Pisa, Special Issue of Linguistica Computazionale Vol. XVIII-XIX (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 IFIP International Federation for Information Processing
About this paper
Cite this paper
Amato, F., Mazzeo, A., Penta, A., Picariello, A. (2008). Knowledge Representation and Management for E-Government Documents. In: Mazzeo, A., Bellini, R., Motta, G. (eds) E-Government Ict Professionalism and Competences Service Science. IFIP International Federation for Information Processing, vol 280. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09712-1_4
Download citation
DOI: https://doi.org/10.1007/978-0-387-09712-1_4
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-09711-4
Online ISBN: 978-0-387-09712-1
eBook Packages: Computer ScienceComputer Science (R0)