WSEAS Transactions on Information Science and Applications


Print ISSN: 1790-0832
E-ISSN: 2224-3402

Volume 14, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.



Ontology Similarity Assessment Based on Lexical and Structural Model Features Extraction

AUTHORS: Mariusz Chmielewski, Małgorzata Paciorkowska, Maciej Kiedrowicz

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ABSTRACT: This work discusses a method for extracting quantitative measures from terminology and instance base components of semantic models. The method introduces a multi-criteria analysis while comparing ontology models and assessing semantic similarity. The article presents theoretical overview of the method and tool implementing evaluation schemes supplemented with practical examples. The capabilities of the method can be used for semantic pattern recognition within knowledge bases, which can be utilised by analytical tools especially in the security domain (criminal threat, financial fraud detection, etc.). The specificity of security applications requires methods dedicated for analysis of hidden, indirect, comprehensive and versatile data. Structural analysis method and its implementation in form of ETOSE plugin for Protégé OWL environment delivers process-based approach for evaluating instance bases. The mechanisms has been designed to operate as a data flow interceptor, collecting the data and transforming them into instances expressed in a specific domain ontology (set of ontology modules). Presented quantitative approach has been applied in terrorist threat assessment, financial fraud identification tasks where certain templates of behaviour and associations can be described. The method and tool utilize structural and lexicon comparison of compared ontologies in order to deliver multi-criteria evaluation of concepts, relationships and indirectly implemented axioms.

KEYWORDS: ETOSE, semantic structural analysis, semantic similarity, ontology, quantitative analysis, similarity measurement, OWL2, Protégé

REFERENCES:

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[3] M. Chmielewski, M. Paciorkowska, M. Kiedrowicz, A semantic similarity evaluation method and a tool utilised in security applications based on ontology structure and lexicon analysis, 21st International Conference on Circuits, Systems, Communications and Computers(CSCC 2017), AgiaPelagiaBeach, Crete Island,Greece, July 14-17, 2017

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[10] Chmielewski M., Stąpor P. (2016) Medical Data Unification Using Ontology-Based Semantic Model Structural Analysis. In: Świątek J., Borzemski L., Grzech A., Wilimowska Z. (eds) Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part III. Advances in Intelligent Systems and Computing, vol 431. Springer, Cham

[11] Chmielewski M., Stąpor P. (2017) Money Laundering Analytics Based on Contextual Analysis. Application of Problem Solving Ontologies in Financial Fraud Identification and Recognition. In: Borzemski L., Grzech A., Świątek J., Wilimowska Z. (eds) Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part I. Advances in Intelligent Systems and Computing, vol 521. Springer, Cham

[12] M. Kiedrowicz, 'The importance of an integration platform within the organization', Zeszyty Naukowe, vol. 46, pp. 83-94, 2014.

[13] M. Kiedrowicz and J. Stanik, 'Selected aspects of risk management in respect of security of the document lifecycle management system with multiple levels of sensitivity', (in:) Information Management in Practice, (eds) B.F. Kubiak and J. Maślankowski, pp. 231-249, 2015.

[14] M. Kiedrowicz, and R. Waszkowski, 'Business rules automation standards in business process management systems', (in:) Information Management in Practice, (eds) B.F. Kubiak and J. Maślankowski, pp. 187-200, 2015.

[15] M. Kiedrowicz, 'Objects identification in the informations models used by information systems', GIS ODYSSEY 2016, pp. 129-136, 2016.

[16] M. Kiedrowicz, T. Nowicki, and R. Waszkowski, 'Business process data flow between automated and human tasks', 3rd International Conference on Social Science (ICSS 2016) December 9–11 2016, pp. 471- 477, 2016.

WSEAS Transactions on Information Science and Applications, ISSN / E-ISSN: 1790-0832 / 2224-3402, Volume 14, 2017, Art. #15, pp. 134-144


Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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