Scientific and Technical Journal

ELECTROTECHNIC AND COMPUTER SYSTEMS

ISSN Print 2221-3937
ISSN Online 2221-3805
СOMPUTER SYSTEM FOR AUTOMATED ONTOLOGY BUILDING BASIC CROCUS
Abstract:

The paper describes an approach to developing a computer system automated build basic ontology.This approachbases to natural language text documents analysis. There is described the method for semantic analysis of documents using the software Link Grammar Parser and machine learning techniques. Machine learning tools operate in conjunction with OWL- ontology. Ontology gives grammatically templates and semantic structures for recognition statements (predicate logic of 1st order) in patients and / or educational texts. As a result of the recognition are new items that are added to the ontology. There is built the architecture synthesis system ontology. The basic modules of the system and their purpose are described. Authors choose the software tools for the practical implementation of the system. There is done the practical implementation of the proposed method. The functionality of the developed system has tested. The system allows in automatic mode to fill the domain ontology.

Authors:
Keywords
DOI
10.15276/etks.13.89.2014.20
References
  1. Ourania Hatzi, Dimitris Vrakas, Nick Bassiliades, Dimosthenis Anagnostopoulos, and Ioannis Vlahavas. The PORSCE II Framework: Using AI Planning for Automated Semantic Web Service Composition. The Knowledge Engineering Review, (2010), Cambridge University Press, Vol. 02:3, pp. 1–24 (InEnglish).
  2. Dosyn D., Lytvyn V., Nikolsky Y., andV. Pasichnyk. Intelektualjnisystemy, bazovaninaontolijah [IntelligentSystemBasedonOntology],(2009),Cyvilizacija,Lviv, Ukrainе, 414 p. (In Ukrainian).
  3. Link Grammar – Carnegie Mellon University, available at: http://bobo.link.cs.cmu.edu/link (accessed 11.02.2014) 
  4. LytvynV., UgrynD. Metodavtomatychnojirozbudovyadaptyvnojiontologiji[MethodofAutomaticOntologyBuildingAdaptive], (2011), VisnykNacionaljnogotehnichnogouniversytetuHPIPubl., Kharkiv, Ukrainе, No. 10, pp. 75 – 82 (InUkrainian).
  5. LytvynV. Avtomatyzacijaprocesurozvytkubazovojiontologijinaosnovianalizutekstovyhresursiv[AutomatingtheProcessofBasicOntologyBasedonAnalysisofTextualResources] (2010), VisnykNacionaljnogouniversytetuLvivskapolitehnikaPubl., Lviv, Ukrainе, No. 673, pp. 319 – 325 (InUkrainian).
  6. Lytvyn V. Design of Intelligent Decision Support Systems using Ontological Approach,(2013),An International Quarterly Journal on Economics in Technology, new Technologies and Modelling Processes,Krakiv-Lviv, Vol. II, No. 1,рр. 31 – 38 (InEnglish).
  7. LytvynV. Bazyznanjintelektualjnyhsystempidtrymkypryjnjattjarishenj [KnowledgeBaseIntelligentDecisionSupportSystems], (2011), Lviv, Ukraine: VydavnyctvoNacionaljnogoUniversytetuLvivskaPolitehnika”, 240 p. (InUkrainian).
  8. Lytvyn V., Dosyn D., and Smolarz A. An Ontology Based Intelligent Diagnostic Systems of Steel Corrosion Protection, (2013), Elektronika, Lodzj, No. 8, 2–13, pp. 22 – 24 (InEnglish).
  9. Lytvyn V.V. The Similarity Metric of Scientific Papers Summaries on the Basis of Adaptive Ontologies, (2011), Proceedings of VIIth International Conference on Perspective Technologies and Methods in MEMS Design, Polyana, Ukraine, 11–14 May 2011, Lviv, IEEE; LPNU, 162 p. (InEnglish).
  10.  Lytvyn V., Shakhovska N., Pasichnyk V., and Dosyn D. Searching the Relevant Precedents Based on Adaptive Ontology, (2011), Proceedings of XII International Workshop Computational Problems of Electrical Engineering, Kostryna, Ukraine, 5–7 September 2011, Lviv, IEEE; LPNU, 43 p. (InEnglish).
  11. Kovalevych V.M., and Lytvyn V.V. Method of evaluationknowledge noveltyduringon-learning ontologies [Metod Ocinuvannja Novyzny Znanj pid chas Navchannja Ontologij], (2013), Vidbir i Obrobka Informaciji, Lviv, Ukraina, No. 39(115), pp. 82 – 90 (InUkrainian).
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2017-11-19 12:05:04

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