Abstract
We introduce a new software solution to the problem of labour- and time-consuming linguistic crossdomain ontological modelling. TSGraph contributes to the interaction of a cognitive linguist with an automatically collected terminological database. The program builds ontology of several knowledge domains and highlights their overlapping in terms of semantic relations of ontological areas. The relations are parsed from Datamuse API, “a word-finding query engine for developers” [1]. TSGraph involves a number of technologies including Java 8, Spring Framework, Maven, and MySql. To build the graph we use the graph visualization library arbor.js which is a library of java script language.
The current version of TSGraph includes terminology of three domains, namely Computer Security, Biology, and Chemistry. The terminological database is collected by means of a supervised machine learning technology, implemented with TSBuilder, which is our previous development. For visual clustering, the terms have attraction points highlighted in different colours and labeled according to the knowledge domains they represent. Links within and between clusters are highlighted in relevant colours. Pop-up windows provide information on term’s semantic relations, specifically semantically related term and the knowledge domain it belongs to.
The app will be useful to linguists to determine crossdomain synonymy. Further efforts are required to add morphological, syntactic, and other types of relations between terms and to extend the number of domains. These are the features, which are in high demand by researchers in the field of cognitive terminology.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Datamuse API. http://www.datamuse.com/api/
Langacker, R.W.: Foundations in Cognitive Grammar: Theoretical Prerequisites, vol. 1. Stanford University Press, Stanford (1987)
Isaeva, E., Burdina, O.: Transdiscursive term transformation: the evidence from cognitive discursive research of the term ‘virus’. In: I Ferrando, I.N. (ed.) Current Approaches to Metaphor Analysis in Discourse, pp. 79–110. De Gruyter, Berlin (2019). https://doi.org/10.1515/9783110629460-005
Gruber, T.: Ontology. In: Liu, L., Tamer Özsu, M. (eds.) Encyclopedia of Database Systems. Springer, New York (2009). http://tomgruber.org/writing/ontology-definition-2007.html
Bakhtin, V.V., Isaeva, E.V.: Developing an algorithm for identification and categorization of scientific terms in natural language text through the elements of artificial intelligence. In: Proceedings of 2018 14th International Scientific-Technical Conference on Actual Problems of Electronic Instrument Engineering, APEIE 2018, pp. 386–390 (2009) https://doi.org/10.1109/apeie.2018.8545317
Bakhtin, V.V., Isaeva, E.V.: New TSBuilder: shifting towards cognition. In: Proceedings of the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019, 28 February 2019, pp. 179–181 (2019) https://doi.org/10.1109/eiconrus.2019.8656917. Art. № 8656917
Isaeva, E.V., Suvorova, V.A., Bakhtin, V.V.: Automatic Documentation Math. Linguistics. 50(3), 104–111 (2016). https://doi.org/10.3103/S0005105516030031. Allerton Press
Gallant, M., Isah, H., Zulkernine, F., Khan, S.: Xu: an automated query expansion and optimization tool. In: 43rd IEEE Annual Computer Software and Applications Conference, COMPSAC 2019; Milwaukee, USA, vol. 1. pp. 443–452 (2019)
Datamuse. https://www.datamuse.com
WordNet. https://wordnet.princeton.edu/
jQuery. https://code.jquery.com/
Arbor.js. http://arborjs.org/
Acknowledgements
The reported study was funded by RFBR according to the research project № 18-012-00825 А.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Isaeva, E., Bakhtin, V., Tararkov, A. (2020). Formal Cross-Domain Ontologization of Human Knowledge. In: Rocha, Á., Ferrás, C., Montenegro Marin, C., Medina García, V. (eds) Information Technology and Systems. ICITS 2020. Advances in Intelligent Systems and Computing, vol 1137. Springer, Cham. https://doi.org/10.1007/978-3-030-40690-5_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-40690-5_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-40689-9
Online ISBN: 978-3-030-40690-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)