KnE Engineering

ISSN: 2518-6841

The latest conference proceedings on all fields of engineering.

Applied Ontologies Formation Based on Subject Area Texts

Published date: Oct 08 2018

Journal Title: KnE Engineering

Issue title: Breakthrough directions of scientific research at MEPhI: Development prospects within the Strategic Academic Units

Pages: 6–17

DOI: 10.18502/keg.v3i6.2965

Authors:
Abstract:

The problems of the formation of applied conceptual systems based on ontologies constructed automatically from the texts of the subject area documents are considered. Algorithms of operations on ontologies using the thesaurus as a general conceptual basis, unifying the terminology of the subject area, are proposed. Experiments with ontology collection obtained from the texts of design documentation showed that the semantic similarity of the resulting concepts of the system can be increased through the use of thesaurus links.

 

 

Keywords: ontologies, thesaurus, operations on ontologies, graph theory, semantic similarity, Neo4j, Java

References:

[1] Meenachi. N. M. and M. Sai Baba. (2017). Matrix rank-based ontology matching: An extension of string equality matching. International Journal of Nuclear Knowledge Management (IJNKM), vol. 7, no. 1, pp. 1–11.


[2] Lyubchenko, V. V. and Kavitskaya, V. S. (2013). Method for determining the equivalence of classes of ontologies, in Proceedings of the Odessa Polytechnic University, vol. 2, no. 41, pp. 242–246.


[3] Biryukov, D. N. and Lomaco, A. G. (2015). Semantics of knowledge contexts in ontological modeling of conflict subject areas, in Proceedings of SPIIRAS, vol. 5, no. 42, pp. 155–179.


[4] Samokhvalov, E. N., Revukov, G. I., and Gapanyuk, Yu. E. (2015). Metagraphs for Information Systems Semantics and Pragmatics Definition. Bulletin of MSTU, vol. 1, pp. 83–89.


[5] Palagin, A., Kryvy, S., and Petrenko, N. (2015). Development, research and presentation of functions and operations on ontologies. International Journal “Information Theories and Applications”, vol. 22, no. 2, pp. 103–114.


[6] Novototskikh, D. V., Romanov, V. P., and Safonova, M. S. (2016). Dynamic structure of modern innovative enterprises. Statistics and Economics, vol. 13, no. 5, pp. 57–62.


[7] Kryvy, S. L. (2016). Formalized ontological models in scientific research. Control Systems and Machines, no. 3, pp. 4–15.


[8] Golitsyna, O. L., Maksimov, N. V., and Okropishina, O. V. (2012). The ontological approach to the identification of information in tasks of document retrieval. Automatic Documentation and Mathematical Linguistics, vol. 46, no. 3, pp. 125–132.


[9] Golitsyna, O. L., Maksimov, N. V., and Fedorova, V. A. (2016). On determining semantic similarity based on relationships of a combined thesaurus. Automatic Documentation and Mathematical Linguistics, vol. 50, no. 4, pp. 139–153.

Download
HTML
Cite
Share
statistics

172 Abstract Views

185 PDF Downloads