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A Learning Approach for Knowledge Acquisition in the Legal Domain

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Book cover Approaches to Legal Ontologies

Part of the book series: Law, Governance and Technology Series ((LGTS,volume 1))

Abstract

In this chapter an approach to support knowledge acquisition in the legal domain is presented: it is based on a semantic model for legislation and implemented using knowledge extraction techniques on legislative texts. This methodology is targeted to propose a framework which can contribute to bridge the gap between consensus and authoritativeness in legal knowledge implementation.

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Notes

  1. 1.

    Folksonomies (or social tagging mechanisms) have been widely implemented in knowledge sharing environments; the idea was first adopted by the social bookmarking site del.icio.us (2004) http://delicious.com

  2. 2.

    “Typically regulations are not given in an empty environment; instead they make use of terminology and concepts which are relevant to the organisation and/or the aspect they seek to regulate. Thus, to be able to capture the meaning of regulations, one needs to encode not only the regulations themselves, but also the underlying ontological knowledge. This knowledge usually includes the terminology used, its basic structure, and integrity constraints that need to be satisfied.” Grigoris Antoniou, David Billington, Guido Governatori, and Michael J. Maher, “On the modeling and analysis of regulations”, in Proceedings of the Australian Conference Information Systems, pages 20–29, 1999.

  3. 3.

    http://www.dalosproject.eu

  4. 4.

    http://www.xmleges.org

  5. 5.

    xmLegesExtractor has been developed in collaboration with the Institute of Computational Linguistics (ILC-CNR) in Pisa (Italy)

References

  • Agnoloni, T., L. Bacci, E. Francesconi, W. Peters, S. Montemagni, G. Venturi (2009). A Two-Level Knowledge Approach to Support Multilingual Legislative Drafting. In J. Breuker, P. Casanovas, M. Klein, E. Francesconi (Eds.) Law, Ontologies and the Semantic Web, vol. 188 of Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam, 177–198.

    Google Scholar 

  • Bacci, L., P. Spinosa, C. Marchetti, R. Battistoni (2009). Automatic Mark-Up of Legislative Documents and Its Application to Parallel Text Generation. In N. Casellas, E. Francesconi, R. Hoekstra, S. Montemagni (Eds.) Proceedings of the 3rd Workshop on Legal Ontologies and Artificial Intelligence Techniques joint with 2nd Workshop on Semantic Processing of Legal Texts. Huygens Editorial, Barcelona, 45–54.

    Google Scholar 

  • Bartolini, R., A. Lenci, S. Montemagni, V. Pirrelli (2002). The Lexicon-Grammar Balance in Robust Parsing of Italian. In Proceedings of 3rd International Conference on Language Resources and Evaluation.

    Google Scholar 

  • Bartolini, R., A. Lenci, S. Montemagni, V. Pirrelli, C. Soria (2004a). Automatic Classification and Analysis of Provisions in Italian Legal Texts: A Case Study. In Proceedings of the Second International Workshop on Regulatory Ontologies.

    Google Scholar 

  • Bartolini, R., A. Lenci, S. Montemagni, C. Soria (2004b). Semantic Mark-Up of Legal Texts Through Nlp-Based Metadata-Oriented Techniques. In Proceedings of 4rd International Conference on Language Resources and Evaluation.

    Google Scholar 

  • Bentham, J., H.L.A. Hart (1970). Of Laws in General. Athlone, London, (1st ed. 1872).

    Google Scholar 

  • Biagioli, C. (1991). Definitional Elements of a Language For Representation of Statutory. Rechtstheorie, 11: 317–336.

    Google Scholar 

  • Biagioli, C. (1997). Towards a Legal Rules Functional Micro-Ontology. In Proceedings ofworkshop LEGONT ’97.

    Google Scholar 

  • Biagioli, C., F. Turchi. (2005). Model and Ontology Based Conceptual Searching in Legislative Xml Collections. In Proceedings of the Workshop on Legal Ontologies and Artificial Intelligence Techniques, 83–89.

    Google Scholar 

  • Biagioli, C., E. Francesconi, A. Passerini, S. Montemagni, C. Soria (2005). Automatic Semantics Extraction in Law Documents. In Proceedings of International Conference on Artificial Intelligence and Law, 133–139.

    Google Scholar 

  • Breuker, J., R. Hoekstra (2004a). Core Concepts Of Law: Taking Common-Sense Seriously. In Proceedings of Formal Ontologies in Information Systems.

    Google Scholar 

  • Breuker, J., R. Hoekstra (2004b). Epistemology and Ontology In Core Ontologies: Folaw and lricore, Two Core Ontologies For Law. In Proceedings of EKAW Workshop on Core ontologies. CEUR.

    Google Scholar 

  • Breuker, J., S. van de Ven, A. El Ali, M. Bron, S. Klarman, U. Milosevic, L. Wortel, A. Forhecz (2008). Developing Harness. ESTRELLA Deliverable 4.6/3b, European Commission.

    Google Scholar 

  • Breuker, J., P. Casanovas, M. Klein, E. Francesconi (Eds.) (2009). Law, Ontologies and the Semantic Web. Channelling the Legal Information Flood, vol. 188 of Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam.

    Google Scholar 

  • Buckley, C., G. Salton (1988). Term-Weighting Approaches in Automatic Text Retrieval. Information Processing and Management, 24(5): 513–523.

    Article  Google Scholar 

  • Buitelaar, P., P. Cimiano (Eds.) (2008). Ontology Learning and Population: Bridging the Gap Between Text and Knowledge, vol. 167 of Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam.

    Google Scholar 

  • Buitelaar, P., P. Cimiano, B. Magnini (2005). Ontology Learning From Text: An Overview. In Buitelaar et al. (Eds.) Ontology Learning from Text: Methods, Evaluation and Applications, vol. 123 of Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam, 3–12.

    Google Scholar 

  • Bylander, T., B. Chandrasekaran (1987). Generic Tasks for Knowledge-Based Reasoning: The “Right” Level Of Abstraction For Knowledge Acquisition. International Journal of Man-Machine Studies, 26(2): 231–243.

    Article  Google Scholar 

  • Bench Capon, T.J.M., P.R.S. Visser (1997). Ontologies in Legal Information Systems; The Need For Explicit Specifications of Domain Conceptualizations. In Proceedings of the 6th International Conference on Artificial Intelligence and Law. ACM Press, New York, NY, 132–141.

    Google Scholar 

  • Casellas, N. (2008). Modelling Legal Knowledge through Ontologies. OPJK: The Ontology of Professional Judicial Knowledge. Ph.D. thesis, Institute of Law and Technology, Autonomous University of Barcelona.

    Google Scholar 

  • Chandrasekaran, B. (1986). Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design. IEEE Expert, 1(3): 23–30.

    Article  Google Scholar 

  • Cimiano, P. (2006). Ontology Learning and Population From Text. In Algorithms, Evaluation and Applications. Springer, Berlin.

    Google Scholar 

  • Clancey, W.J. (1981). The Epistemology of a Rule-Based Expert System: A Framework for Explanation. Technical Report STAN-CS-81-896, Stanford University, Department of Computer Science.

    Google Scholar 

  • Euzenat, J., P. Shvaiko (2007). Ontology Matching. Springer, Berlin.

    Google Scholar 

  • Francesconi, E., A. Passerini (2007). Automatic Classification of Provisions in Legislative Texts. International Journal on Artificial Intelligence and Law, 15(1): 1–17.

    Article  Google Scholar 

  • Francesconi, E., S. Faro, E. Marinai (2008). Thesauri Alignment for Eu Egovernment Services: A Methodological Framework. In Proceedings of the JURIX 2008 Conference. IOS Press, Amsterdam, 73–77.

    Google Scholar 

  • Gangemi, A., N. Guarino, C. Masolo, A. Oltramari, L. Schneider (2002). Sweetening Ontologies With Dolce. In A. Gangemi, N. Guarino, C. Masolo, A. Oltramari, L. Schneider (Eds.) Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management (EKAW02), LNCS, vol. 2473.

    Google Scholar 

  • Gruber, T. (2006). Where the Social Web Meets the Semantic Web (Keynote Abstract). In I.F. Cruz, S. Decker, D. Allemang, C. Preist, D. Schwabe, P. Mika, M. Uschold, L. Aroyo (Eds.) The Semantic Web – ISWC 2006, Proceedings of the 5th International Semantic Web Conference, LNCS, vol. 4273. Springer, Berlin, 994.

    Chapter  Google Scholar 

  • Guarino, N. (1997). Semantic Matching: Formal Ontological Distinctions For Information Organization, Extraction, and Integration. In M.T. Pazienza (Ed.) Information Extraction: A Multidisciplinary Approach to an Emerging Information Technology, LNCS, vol. 1299. Springer, Berlin, 139–170.

    Google Scholar 

  • Hart, H. (1961). The Concept of Law. Clarendon Law Series. Oxford University Press, Oxford.

    Google Scholar 

  • Hoekstra, R., J. Breuker, M. Bello, A. Boer (2009). Lkif Core: Principled Ontology Development for the Legal Domain. In J. Breuker, P. Casanovas, M. Klein, E. Francesconi (Eds.) Legal Ontologies and the Semantic Web. IOS Press, Amsterdam.

    Google Scholar 

  • Hohfeld, W.N. (1913). Some Fundamental Legal Conceptions as Applied in Judicial Reasoning. I. Yale Law Journal, 23: 16–59.

    Article  Google Scholar 

  • Hohfeld, W.N. (1917). Some Fundamental Legal Conceptions as Applied in Judicial Reasoning. II. Yale Law Journal, 26: 710–770.

    Article  Google Scholar 

  • Kelsen, H. (1991). General Theory of Norms. Clarendon Press, Oxford.

    Google Scholar 

  • Lame, G. (2005). Using Nlp Techniques to Identify Legal Ontology Components: Concepts and Relations. Lecture Notes in Computer Science, 3369: 169–184.

    Google Scholar 

  • Lenci, A., S. Montemagni, V. Pirrelli, G. Venturi (2009). Ontology Learning from Italian Legal Texts. In J. Breuker, P. Casanovas, M. Klein, E. Francesconi (Eds.) Law, Ontologies and the Semantic Web, vol. 188 of Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam, 7594.

    Google Scholar 

  • Quinlan, J.R. (1986). Inductive Learning of Decision Trees. Machine Learning, 1: 81–106.

    Google Scholar 

  • Rawls, J. (1955). Two Concepts of Rule. Philosophical Review, 64: 3–31.

    Article  Google Scholar 

  • Raz, J. (1977). Il Concetto di Sistema Giuridico. Il Mulino, Bologna.

    Google Scholar 

  • Ricciardi, M. (1997). Constitutive Rules and Institutions. In Meeting ofthe Irish Philosophical Club and the Royal Institute ofPhilosophy, Ballymanscanlon.

    Google Scholar 

  • Ross, A. (1968). Directives and Norms. Routledge, London.

    Google Scholar 

  • Saias, J., P. Quaresma (2005). A Methodology to Create Legal Ontologies in a Logic Programming Based Web Information Retrieval System. Lecture Notes in Computer Science, 3369: 185–200.

    Google Scholar 

  • Searle, J.R. (1969). Speech Acts: An Essay in the Philosophy of Language. Cambridge University Press, Cambridge, MA.

    Google Scholar 

  • Sebastiani, F. (2002). Machine Learning in Automated Text Categorization. ACM Computing Surveys, 34(1): 1–47. URL http://faure.iei.pi.cnr.it/fabrizio/Publications/ACMCS02.pdf.

  • Studer, R., V. R. Benjamins, D. Fensel (1998). Knowledge Engineering: Principle and Methods. Data Knowledge Engineering, 25(1–2): 161–197.

    Article  Google Scholar 

  • van Heijst, G. (1995). The Role of Ontologies in Knowledge Engineering. Ph.D. thesis, Social Science Informatics, University of Amsterdam.

    Google Scholar 

  • Walter, S., M. Pinkal (2006). Automatic Extraction of Definitions From German Court Decisions. In Proceedings of the COLING-2006 Workshop on Information Extraction Beyond The Document, Sidney, 20–28.

    Google Scholar 

  • Walter, S., M. Pinkal (2009). Definitions in Court Decisions – Automatic Extraction and Ontology Acquisition. In J. Breuker, P. Casanovas, M. Klein, E. Francesconi (Eds.) Law, Ontologies and the Semantic Web, vol. 188 of Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam, 95–113.

    Google Scholar 

  • Yang, Y., J.O. Pedersen (1997). A Comparative Study on Feature Selection in Text Categorization. In Proceedings of the Fourteenth International Conference on Machine Learning. Morgan Kaufmann Publishers Inc., San Mateo, CA, 412–420.

    Google Scholar 

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Author information

Authors and Affiliations

  1. ITTIG-CNR – Institute of Legal Information Theory and Techniques, Italian National Research Council, Torino, Italy

    Enrico Francesconi

Authors
  1. Enrico Francesconi
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Correspondence to Enrico Francesconi .

Editor information

Editors and Affiliations

  1. European University Institute, Via Boccaccio, Villa Schifanoia 121, Florence, 50133, Italy

    Giovanni Sartor

  2. Institut de Dret i Tecnologia, Universitat Autònoma de Barcelona, Barcelona, 08193, Spain

    Pompeu Casanovas

  3. Ittig- CNR, Via dei Barucci 20, Firenze, 50127, Italy

    Mariangela Biasiotti

  4. Facultat de Dret, Institut de Dret i Tecnologia, Campus UAB, Edifici B, Barcelona - Bellaterra, 08193, Spain

    Meritxell Fernández-Barrera

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Francesconi, E. (2011). A Learning Approach for Knowledge Acquisition in the Legal Domain. In: Sartor, G., Casanovas, P., Biasiotti, M., Fernández-Barrera, M. (eds) Approaches to Legal Ontologies. Law, Governance and Technology Series, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0120-5_13

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