S.O. Kosenko,
post-graduate student The Georgy Pukhov Institute
for Energy Modelling of NAS of Ukraine;
(Ukraine, 03164, Kyiv, 15, General Naumov Str.,
e-mail:
Èlektron. model. 2018, 40(1):93-114
https://doi.org/10.15407/emodel.40.01.093
АННОТАЦИЯ
Подано загальні відомості про походження поняття «онтологія» та проаналізовано шляхи його подальшої трансформації для використання в системах штучного інтелекту, де онтологія розглядається як комплекс знань, що надають певну інформацію про об’єкт дослідження. На теперішній час розроблено низку різноманітних онтологій, а саме поверхневі, топові, доменні тощо, котрі є основою при розробці системи штучного інтелекту з використанням накопичених знань та баз даних для удосконалення процесу логічного мислення і прийняття відповідних рішень. Особливого значення набули онтології в правознавстві для формалізації законів, прийняття судових рішень та надання інформації про певні прецеденти та нетипові випадкі. Наведено критерії дизайну онтологій, а також
особливості їх застосування в правовому домені. Формування онтологій має специфічні завдання, однак відсутні які-небудь способи формування їх змісту та дизайну. Головне завдання, якого слід дотримуватися при створенні онтології, полягає у суворому і чіткому формулюванні суті онтології, враховуючи зв’язок між різними онтологіями.
КЛЮЧЕВЫЕ СЛОВА:
онтологія, право, штучний інтелект, концептуалізація, правовий домен.
СПИСОК ЛИТЕРАТУРЫ
1. Genesereth, M.R. and Nilsson, N.J. (1988), Logical foundations of artificial intelligence, Morgan Kaufmann Publishers, California, USA.
2. Fulton, J.A. (1992), Standards working document ISO TC184/SC4/WG3 N103, IGES/PDSES Organization, Dictionary/Methodology Committee, USA, Technical report on the semantic unification meta-model.
3. Enderton, H.B. (1972), A mathematical introduction to logic, Academic Press, San Diego, USA.
4. Newell, R.R. (1982), The knowledge level, Artificial Intelligence, Vol. 18, no. 1, pp. 87-127, HYPERLINK «https://doi.org/10.1016/0004-3702%2882%2990012-1" \o »Persistent link using digital object identifier" \t «_blank» doi: 10.1016/0004-3702(82)90012-1.
5. Levesque, H.J. (1984), Foundations of a functional approach to knowledge representation, Artificial Intelligence, Vol. 23, no. 1, pp. 155-212, available at: HYPERLINK «https://doi.org/10.1016/0004-3702%2884%2990009-2" \o »Persistent link using digital object identifier" \t «_blank» doi: 10.1016/0004-3702(84)90009-2.
6. Gruber, T.R. (1995), Toward principles for the design of ontologies used for knowledge sharing, Int. Journal of Human-Computer Studies, Vol. 43, pp. 907-928, available at: HYPERLINK «https://doi.org/10.1006/ijhc.1995.1081" \o »Persistent link using digital object identifier" \t «_blank» doi: 10.1006/ijhc.1995.1081.
7. McCarty, L.T. (2002), Ownership: A case study in representing legal concepts, Artificial Intelligence and Law, Vol. 10, pp. 135-161, doi:10.1023/A:1019584605638.
8. Genesereth, M.R. and Fikes, R.E. (1992), Knowledge interchange format, Version 3.0, Reference Manual, Tech. Rep. Logic-92-1, Computer Science Department, Stanford University, USA, doi: 10.1.1.54.8601.
9. Bench-Capon, T.J.M. and Visser, P.R.S. (1997), Ontologies in legal information systems; the need for explicit specifications of domain conceptualisations, Proceedings of the Sixth International Conference on Artificial Intelligence and Law (ICAIL ’97), Melbourne, Australia, 1997, pp.132-141, doi: HYPERLINK «https://doi.org/10.1145/261618.261646" \t »_self" 10.1145/261618.261646.
10. Noy, N.F., Fergerson, R.W. and Musen, M.A. (2000), The knowledge model of Protege-2000: Combining interoperability and flexibility, Proceedings of the 12th International Conference on Knowledge Engineering and Knowledge Management (EKAM 2000), Juanles-Pins, France, 2000, pp. 87-98, doi: 10.1007/3-540-39967-4_2.
11. Visser, P.R.S. (1995), Knowledge specification for multiple tasks, Kluwer Law International Hague, Boston, USA.
12. Bench-Capon, T. and Jones, D. (1999), PRONTO: Ontology based evaluation of knowledge based systems, Validation and verification of knowledge based systems, Eds A. Vermesan and F. Coenen, Kluwer Academic Publishers, Dordrecht, Boston, USA, doi: 10.1007/978-1-4757-6916-6_7.
13. Aleven, V. (1997), Teaching case based argumentation through an example and models, PhD Thesis, The University of Pittsburgh, Pittsburg, USA, doi: 10.1.1.203.1165.
14. Ashley, K.D. (1990), Modeling legal argument, MIT Press, Cambridge, MA, USA.
15. Prakken, H. and Sartor, G. (1998), Modeling reasoning with precedents in a formal dialogue game, Artificial Intelligence and Law,Vol. 6, pp. 231-287, doi: 10.1007/978-94-015-9010-5_5.
16. Ashley, K.D. and Bridewell, W. (2010), Emerging AI and law approaches to automating analysis and retrieval of electronically stored information in discovery proceedings, Artificial Intelligence and Law, Vol. 18, pp. 311-320, doi: 10.1007/s10506-010-9098-4.
17. Bench-Capon, T. and Sartor, G. (2003), A model of legal reasoning with cases incorporating theories and values, Artificial Intelligence, Vol. 150, pp. 97-143, doi: HYPERLINK «https://doi.org/10.1016/S0004-3702%2803%2900108-5" \o »Persistent link using digital object identifier" \t «_blank» 10.1016/S0004-3702(03)00108-5.
18. Miller, G.A., Beckwith, R., Fellbaum, Ch., Gross, D. and Miller, K.J. (1990), Introduction to WordNet: an on-line lexical database, International Journal of Lexicography, Vol. 3, no. 4, pp. 361-373, doi: 10.1.1.105.1244.
19. Guha, R.V., Lenat, D.B., Pittman, K., Pratt, D. and Shepherd, M. (1990), CYC: A midterm report, Communications of the ACM,Vol. 33, no. 8, pp. 345-357, doi: 10.1080/08839519108927917.
20. Valente, A. (1995), Legal knowledge engineering: A modelling approach, IOS Press, Amsterdam, Netherlands.
21. van Kralingen, R., Visser, P.R.S., Bench-Capon, T.J.M. and van der Herik, J. (1999), A principled methodology for the development of legal knowledge systems, International Journal of Human Computer Studies, Vol. 51, no. 6, pp. 1127-1154, doi: HYPERLINK «https://doi.org/10.1006/ijhc.1999.0300" \o »Persistent link using digital object identifier" \t «_blank» 10.1006/ijhc.1999.0300.
22. McCarty, L.T. (1989), A language for legal discourse I. Basic features, Proceedings of the Second International Conference on Artificial Intelligence and Law, New York, 1989, pp.180-189, doi: HYPERLINK «https://doi.org/10.1145/74014.74037" \t »_self" 10.1145/74014.74037.
23. McCarty, L.T. (2007), Deep semantic interpretations of legal texts, Proceedings of the Eleventh International Conference on Artificial Intelligence and Law, Stanford, CA, 2007, pp. 217-224,
doi: HYPERLINK «https://doi.org/10.1145/1276318.1276361" \t »_self" 10.1145/ 1276318.
1276361.
24. Stamper, R.K. (1991), The role of semantics in legal expert systems and legal reasoning, Ratio
Jurist, Vol. 4, no. 2, pp. 219-244, doi: 10.1111/j.1467-9337.1991.tb00094.x
25. Gruber, T.R. (1992), ONTOLINGUA:Amechanismto support portable ontologies,Knowledge systems laboratory, Tech. Rep., Stanford University, California, USA, doi: 10.1.1.34.9819.
26. Valente, A. andBreuker, J. (1999), Legalmodeling and automated reasoning with ON-LINE, International
Journal of Human-Computer Studies, Vol. 51, no. 6, pp. 1079-1125, doi: HYPERLINK «https://doi.org/10.1006/ijhc.1999.0298" \o »Persistent link using digital object identifier" \t «_blank» 10.1006/ijhc.1999.0298.
27. Valente, A. (2006), Types and roles of legal ontologies, Law and Semantic Web. LNAI 3369, Ed V.R. Benjamins, Springer Verlag, Berlin, Germany, doi: 10.1007/978-3-540-32253-5_5.
28. Valente, A. and Breuker, J. (1994), A functional ontology of law, Towards a global expert system in law, Eds. G. Bargellini and S. Binazzi, CEDAM Publishers, Padua, Italy, doi: 10.1.1.39.8951.
29. Visser, P. and Bench-Capon, T. (1998), Acomparison of four ontologies for the design of legal knowledge systems, Artificial Intelligence and Law, Vol. 6, no. 1, pp. 54-68, doi: 10.1023/A:1008251913710
30. Bolioli, A., Dini, L., Mercatali, P. and Romano, F. (2002), For the automated mark-up of Italian legislative texts in XML, Legal Knowledge and Information Systems JURIX 2002: The Fifteenth Annual Conference, Eds. T. Bench-Capon, A. Daskalopulu, and R. Winkels, IOS Press, Amsterdam, Netherlands, pp. 21-30, doi: 10.1.1.106.6559.
31. Breuker, J., Elhag, A., Petkov, E. and Winkels, R. (2002), Ontologies for legal information serving and knowledge management, Legal Knowledge and Information Systems JURIX 2002: The Fifteenth Annual Conference, Eds. T. Bench-Capon, A. Daskalopulu, and R. Winkels, IOS Press, Amsterdam, Netherlands, pp. 73-82, doi: 10.1.1.59.1956.
32. van Engers, T.M., Gerrits, R., Boekenoogen, M., Glassee, E. and Kordelaar, P. (2001), POWER: using UML/OCL for modeling legislation - an application report, Proceedings of the 8th International Conference on Artificial intelligence and Law, ACM Press, New York, USA, pp. 157-167, doi: HYPERLINK «https://doi.org/10.1145/383535.383554" \t »_self" 10.1145/383535.383554.
33. Delgado, J., Gallego, I., Lorente, S. and Garcia, R. (2003), iPRONTO: An ontology for digital rights management, Legal Knowledge and Information Systems JURIX 2003: The Sixteenth Annual Conference, Ed. D. Bourcier, IOS Press, Amsterdam, Netherlands, pp. 111-121.
34. Sergot, M.J., Sadri, F., Kowalski, R.A., Kriwaczek, F., Hammond, P. and Cory, H.T. (1986), The British nationality act as a logic program, Communications of the ACM, Vo1. 29, no. 5, pp. 370-386, doi: HYPERLINK «https://doi.org/10.1145/5689.5920" \t »_self" 10.1145/5689.5920.
35. Sergot, M.J. (1991), The representation of law in computer programs, Knowledge Based Systems and Legal Applications, Ed. T.J.M. Bench-Capon, Academic Press, London, UK.
36. Kowalski, R.A. (1989), The treatment of negation in logic programs for representing legislation,
Proceedings of the Second International Conference on AI and Law, ACM Press, New York, USA, pp. 48-69, doi: HYPERLINK «https://doi.org/10.1145/74014.74016" \t »_self" 10.1145/74014.74016.
37. Bench-Capon, T.J.M. (1991), Practical legal expert systems: the relation between a formalisation of law and expert knowledge, Computers, Law and AZ, Eds. J. Bennun and M. Narayanan, Ablex, New York, USA, pp. 191-201.
38. McCarty, L.T. (1995), An implementation of Eisner vs Macomber, Proceedings of the Fifth International Conference on AI and Law, ACM Press, New York, USA, pp. 276-286, doi: HYPERLINK «https://doi.org/10.1145/222092.222258" \t »_self" 10.1145/222092.222258.
39. Moles, R.N. and Dayal, S. (1992), There is more to life than logic, Journal of Information Science, Vol. 3, no. 2, pp.188-218.
40. Wyner, A. (2008), An ontology in OWL for legal case-based reasoning, Artificial Intelligence and Law, Vol. 16, pp. 271-283, doi: 10.1007/s10506-008-9070-8.
41. Prakken, H. (2006), Artificial intelligence and law, logic and argument schemes, Arguing on the Toulmin Model, Eds D. Hitchcock and B. Verheij, Dordrecht Springer, Berlin, Germany, pp. 91-117, doi: 10.1007/978-1-4020-4938-5_15.
42. Ashley, K. and Bruninghaus, S. (2009), Automatically classifying case texts and predicting outcomes, Artificial Intelligence and Law, Vol. 17, no. 2, pp. 125-165, doi: 10.1007/s10506-009-9077-9/
KOSENKO Serhii Oleksandrovich, post-graduate student of the Georgy Pukhov Institute for Energy Modelling of NAS of Ukraine; graduated from Yuriy Fedkovych Chernivtsi National University in 1997. The field of research: artificial intelligence.