doi: 10.17586/2226-1494-2017-17-4-711-718


N. F. Gusarova, V. V. Sysoeva

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For citation: Gusarova N.F., Sysoeva V.V. Ontological modeling of semi-structured subject domain with fuzzy logic application. Scientific and Technical Journal of Information Technologies, Mechanics and Optics , 2017, vol. 17, no. 4, pp. 711–718 (in Russian). doi: 10.17586/2226-1494-2017-17-4-711-718


The paper deals with formation and analysis of the semi-structured subject domain with the use of ontological model and  the study of fuzzy logic problems in this subject domain. The main classes and structural links of subject domain are formed, and ontology is realized in Protégé editor by hierarchical construction of entities. We give the examples of ontological model description by means of the OWL language and  describe the access technology to ontology elements through the SPARQL queries language. Basic aspects of fuzzy logic are analyzed. Advantages of fuzzy logic application in ontology creation are listed including the membership function construction with the use of fuzzy modeling tool such as Fuzzy Logic Toolbox with respect to the processunder consideration. We form fuzzy inference system that gives the possibility to estimate a degree of membership for input and output variables to the process under consideration. Ontology for planning a ship repairing process is presented as an example, particularly, sub-process of document coordination. Proposed technology makes it possible to develop and analyze models with varying degree of accuracy in conditions of uncertainty.

Keywords: ontology, ontological model, membership function, OWL, SPARQL, fuzzy logic, fuzzy inference, shipping

 1.     Rybin V.V. Fundamentals of the Theory of Fuzzy Sets and Fuzzy Logic. Moscow, MAI Publ., 2007, 96 p. (In Russian)
2.     Park J.-H., Kim K.-H., Bae J.-H.J. Analysis of shipbuilding fabrication process with enterprise ontology. Computers in Human Behavior, 2011, vol. 27, no. 5, pp. 1519–1526. doi: 10.1016/j.chb.2010.10.021
3.     Kozyrev I.V. Using ontologies in ships operation tasks. Software & Systems, 2013, no. 2, pp. 16–21. (In Russian)
4.     Vatian A., Gusarova N., Artemova G., Dobrenko N. An ontology approach to storing educational information. Proc. Int. FRUCT Conference on Intelligence, Social Media and Web, ISMW FRUCT. St. Petersburg, 2016, art.7584772. doi: 10.1109/FRUCT.2016.7584772
5.     Beresnev A.D., Gusarova N.F., Sysoeva V.V. Formation of ontology of innovative subject domain for use in learning management systems. Distance and Virtual Learning, 2016, no. 8, pp. 89–102. (In Russian)
6.     Sosinskaya S.S. Representation of Knowledge in the Information System. Methods of Artificial Intelligence and Knowledge Representation. Staryi Oskol, TNT Publ., 2011, 215 p. (In Russian)
7.     Kurzaeva L.V. Fuzzy Logic and Neural Networks in the Tasks of Managing Socio-Economic Systems and Processes. Magnitogorsk, NMSTU Publ., 2016, 113 p. (In Russian)
8.     Gromov Yu.Yu., Alekseev V.V., Ivanova O.G., Ivanovskii M.A., Martem'yanov Yu.F., Odnol'ko V.G. Informal Models of Knowledge Representation. Tambov,Nobelistika Publ., 2012, 93 p. (In Russian)
9.     Morozova O.I., Sokolov A.Yu., Khussein V.M. Method of fuzzy structural analysis of ontologies. Sistemy Obrabotki Informatsii, 2010, no. 5, pp. 104–107. (In Russian)
10.  Gavrilova T.A., Kudryavtsev D.V., Muromtsev D.I. Knowledge Engineering. Models and Methods. St. Petersburg, Lan' Publ., 2016, 324 p. (In Russian)
11.  Giorgos Stoilos, Tassos Venetis, Giorgos Stamou, A fuzzy extension to the OWL 2 RL ontology language. Computer Journal,2015,vol. 58, no. 11, pp.2956–2971.doi: 10.1093/comjnl/bxv028
12.  Dobrov B.V., Ivanov V.V., Lukashevich N.V., Solov'ev V.D. Ontologies and Thesauruses: Models, Tools, Applications. Moscow, Binom Publ., 2009, 173 p. (In Russian)
13.  Gegov A. Complexity management in fuzzy systems: a rule base compression approach. International Journal of Hybrid Intelligent Systems, 2008, vol. 5, no. 1, pp. 55. doi: 10.3233/his-2008-5105 
14.  Bobillo F., Straccia U. Representing fuzzy ontology in OWL 2. Proc. IEEE World Congress on Computational Intelligence. Barcelona, Spain, 2010. doi: 10.1109/FUZZY.2010.5584661
15.  Jones T.M. AI Application Programming. Charles River Media, 2005, 473 p.
16.  Kondrat'ev S.I. Methods of Automatic Control of Ships. St. Petersburg, SPbSPU Publ., 2002. (In Russian)
17.  Nilavu D., Sivakumar R. Knowledge representation using type-2 fuzzy rough ontologies in ontology web language. Fuzzy Information and Engineering, 2015,vol. 7, no. 1. doi: 10.1016/j.fiae.2015.03.006 
18.  Straccia U. A fuzzy description logic for the semantic web. In: Capturing Intelligence, 2006, vol. 1, pp. 73–90. doi: 10.1016/S1574-9576(06)80006-7

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