Decision support methods in a competitive environment based on Boyd cycle by means of ontology use

• Autorzy: Lytvyn V. , Oborska O. , Demchuk A. , Krupa D.
• Języki publikacji: EN

Abstrakty

EN

The method of decision making system elaboration in competitive environment based on ontological approach was developed. For scientific modeling of decision support process in competitive environment, mathematical support and methods of domain-specific ontology in the Boyd cycle (OODA – observation, orientation, decision, action) were elaborated.

Słowa kluczowe

EN

decision support system (DSS); ontology; knowledge database; Boyd cycle (OODA); observation; orientation; decision; action; genetic algorithms; expected value; probability

PL

system wspomagania decyzji (DSS); ontologia; technologiczna baza wiedzy; cykl Boyd'a OODA; obserwacja; orientacja; decyzja; akcja; algorytm genetyczny; wartość oczekiwana; prawdopodobieństwo

• Wydawca: Polish Academy of Sciences, Branch in Lublin
• Czasopismo: ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
• Rocznik: 2017
• Tom: Vol. 6, No 2
• Strony: 21--26
• Opis fizyczny: Bibliogr. 31 poz., rys., wz.

Twórcy

autor

Lytvyn V.

• Lviv Polytechnic National University

autor

Oborska O.

• Lviv Polytechnic National University

autor

Demchuk A.

• Lviv Polytechnic National University

autor

Krupa D.

• Lviv Polytechnic National University

Bibliografia

• 1. Gruber T. A. 1993. Translation approach to portable ontologies. Knowledge Acquisition, No. 5 (2), рр. 199–220.
• 2. Guarino N. 1995. Formal Ontology, Conceptual Analysis and Knowledge Representation. International Journal of Human-Computer Studies, 43 (5–6), рр. 625–640.
• 3. Sowa J. 1992. Conceptual Graphs as a universal knowledge representation. In: Semantic Networks in Artificial Intelligence, Spec. Issue of An International Journal Computers & Mathematics with Applications. (Ed. F. Lehmann), No. 2–5, рр. 75–95.
• 4. Montes-y-Gómez M. 2000 Comparison of Conceptual Graphs. Lecture Notes in Artificial Intelligence, Vol. 1793. – Springer-Verlag. Mode of access: http://ccc.inaoep.mx/~mmontesg/publicaciones/2000/ComparisonCG.
• 5. Muller H. M., Kenny E. E., Sternberg P. W. 2004. “An Ontology-Based Information Retrieval and Extraction System for Biological Literature”. PLoS Biol. 2(11):e309. doi:10.1371/journal.pbio.0020309.
• 6. Lytvyn V., Medykovskyj M., Shakhovska N., Dosyn D. 2012 “Intelligent Agent on the Basis of Adaptive Ontologies”. Journal of Applied Computer Science, Vol. 20, No. 2, рр. 71–77.
• 7. Knappe R., Bulskov H., Andreasen T. (2004) Perspectives on Ontology-based Querying // International Journal of Intelligent Systems. – http://akira.ruc.dk/~knappe/publications/ijis2004.pdf.
• 8. Jacso, Peter. 2010. “The impact of Eugene Garfield through the prizm of Web of Science”, Annals of Library and Information Studies, Vol. 57, September 2010, рр. 222.
• 9. Christoph Meinel Serge Linckels 2007 Semantic interpretation of natural language user input to improve search in multimedia knowledge base // Information Technologies, 49(1), рр. 40–48.
• 10. Dosyn D., Lytvyn V., Yatsenko A. 2012 DPoptimization of steel corrosion protection techniques in the intelligent diagnostic system // Physicochemical Mechanics of Materials, Lviv, 2012, No. 9, рр. 329–333.
• 11. Lytvyn V., Medykovskyj M., Shakhovska N., Dosyn D. 2012 Intelligent Agent on the Basis of Adaptive Ontologies // JOURNAL OF COMPUTER SCIENCE, 2012, Vol. 20, No. 2, рр. 71–77.
• 12. Lytvyn V. 2013 Design of intelligent decision support systems using ontological approach // An international quarterly journal on economics in technology, new technologies and modelling processes. – Lublin-Lviv, 2013, Vol. II, No. 1, рр. 31–38.
• 13. Lytvyn V., Dosyn D., Smolarz A. 2013 An ontology based intelligent diagnostic systems of steel corrosion protection // Elektronika. – Poland, Nо. 8b, 2013, рр. 22–24.
• 14. Lytvyn V. Semotuyk O., Moroz O. 2013 Definition of the semantic metrics on the basis of thesaurus of subject area // An international quarterly journal on economics in technology, new technologies and modelling processes, Lublin-Lviv, 2013, Vol. II, No. 4, рр. 47–51.
• 15. Giorgos Stoilos, Giorgos Stamou, and Stefanos Kollias 2005 A String Metric For Ontology Alignment // In Yolanda Gil, Enrico Motta, V. Richard Benjamins, and Mark A. Musen, editors, Proceedings of the 4rd International Semantic Web Conference (ISWC), Vol. 3729 of LNCS, Springer Berlin, рр. 624–637.
• 16. Qiu Ji, Peter Haase, and Guilin Qi 2008 Combination of Similarity Measures in Ontology Matching using the OWA Operator // In Proceedings of the 12th International Conference on Information Processing and Management of Uncertainty in Knowledge-Base Systems (IPMU’08).
• 17. Dosyn D., Lytvyn V., Kovalevych V., Oborska O., Holoshchuk R. 2016 Knowledge Discovery as Planning Development in Knowledgebase Framework // XIIIth 2016 International Conference “Modern Problems of Radio Engineering, Telecommunications and Computer Science”, рр. 449–451.
• 18. Lytvyn V., Vysotska V., Veres O., Rishnyak I., Rishnyak H. 2016 Classification Methods of Text Documents Using Ontology Based Approach. Volume 512 of the series Advances in Intelligent Systems and Computing, рр. 229–240.
• 19. Lytvyn V., Vysotska V., Chyrun L., Chyrun L. 2016 Distance learning method for modern youth promotion and involvement in independent scientific researches // DATA STREAM MINING & PROCESSING. Proceedings of the 2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP), August 23–27, 2016, Lviv, Ukraine, рр. 269–274.
• 20. Chen J., Dosyn D., Lytvyn V., Sachenko A. 2016 Smart Data Integration by Goal Driven Ontology Learning // Advances in Big Data. Advances in Intelligent Systems and Computing, Springer International Publishing AG 2016, рр. 283–292.
• 21. Lytvyn V. , Hopyak M. , Oborska O. 2014 Method of automated development and evaluation of ontologie’s qualities of knowledge // Аpplied- Computer-Science / Instytut Technologicznych Systemow Informacyjnych ; Politechnika Lubelska. – Lublin, Poland, 2014, Vol. 10, No. 4, рр. 26–37.
• 22. Lytvyn V., Oborska O. 2014 Inteligent agents based on adaptive ontology // Fourth International Scientific Conference of Students, and Young Scientists “Theoretical and applied aspects of cybernetics” (TAAC-2014), Taras Shevchenko National University of Kyiv – November 24–28, 2014, Kyiv, Ukraine, рр. 264–273.
• 23. Oborska O., Khrushch S. 2014 The problem of building automated ontology base // 9th International Scientific and Technical Conference “Computer Sciences and Information Technologies” (CSIT- 2014), Lviv Polytechnic National University : November 18–22, 2014, Lviv, Ukraine, р. 113.
• 24. Lytvyn V., Dosyn D., Vovnjanka R., Hopyak M., Oborska O. 2015 Method development and quality evaluation of an ontology // XIIIth International Conference “The Experience of Designing and Application of CAD Systems in Microelectronics”, Polyana-Svalyava (Zakarpattya) : February 24–27, 2015, Lviv, Ukraine, рр. 113–115.
• 25. Euzenat J., McIlraith S., Plexousakis D., Harmelen F. 2004 An API for Ontology Alignment. // Proceedings of the 3rd International Semantic Web Conference, Vol. 3298 of LNCS, Berlin, Springer, 2004, рр. 698–712.
• 26. BIAO Q. 2008 Graph-based Query Rewriting for Knowledge Sharing between Peer Ontologies. // Information Sciences, 178(18), Canada, 2008, рр. 3525–3542.
• 27. Baader F., Calvanese D., Mcguinness D., Nardi D., Patel-Schneider P. 2003 The Description Logic Handbook // Theory, Implementation, and Applications. Cambridge, University Press, 2003.
• 28. Donini F., Nardi D., Rosati R. 2002 Description Logics of Minimal Knowledge and Negation as Failure // ACM Transactions on Computational Logic, 3(2), 2002, рр. 177–225.
• 29. Lytvyn, V. 2009 Multiagent decision support system based on precedent and use adaptive ontology //Electronics, Informatics, Management. Zaporizhzhia, No. 2 (21), 2009, рр. 120–126.
• 30. Andreev, A., Berezkyn, D., Syuzev, V., Shabanov, V. 2003 Models and methods of automatic classification of text sudden-dock. // Vestn. Bauman. Avg. Pryborostroenye. Publishing House of Bauman, 2003, Moscow, No. 3, рр. 45–51.
• 31. Darewych, R., Dosyn, D., Lytvyn, V., Nazarchuk, Z. 2006 Assessment of the similarity of text documents based on the weight of items using information knowledge base // Artif. Intell. Donetsk, Vol. 3, рр. 500–509.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).