Ontology-based spatial pattern recognition in diagrams
| dc.contributor.author | Thomas, Anitta | |
| dc.contributor.author | Gerber, Aurona Jacoba | |
| dc.contributor.author | Van der Merwe, Alta | |
| dc.date.accessioned | 2018-08-07T11:24:43Z | |
| dc.date.issued | 2018-05 | |
| dc.description.abstract | Diagrams are widely used in our day to day communication. A knowledge of the spatial patterns used in diagrams is essential to read and understand them. In the context of diagrams, spatial patterns mean accepted spatial arrangements of graphical and textual elements used to represent diagram-specific concepts. In order to assist with the automated understanding of diagrams by computer applications, this paper presents an ontology-based approach to recognise diagram-specific concepts from the spatial patterns in diagrams. Specifically, relevant spatial patterns of diagrams are encoded in an ontology, and the automated instance classification feature of the ontology reasoners is utilised to map spatial patterns to diagram-specific concepts depicted in a diagram. A prototype of this approach to support automated recognition of UML and domain concepts from class diagrams and its performance are also discussed in this paper. This paper concludes with a reflection of the strengths and limitations of the proposed approach. | en_ZA |
| dc.description.department | Informatics | en_ZA |
| dc.description.embargo | 2019-05-22 | |
| dc.description.librarian | hj2018 | en_ZA |
| dc.description.uri | https://link.springer.com/bookseries/6102 | en_ZA |
| dc.identifier.citation | Thomas A., Gerber A.J., van der Merwe A. (2018) Ontology-Based Spatial Pattern Recognition in Diagrams. In: Iliadis L., Maglogiannis I., Plagianakos V. (eds) Artificial Intelligence Applications and Innovations. AIAI 2018. IFIP Advances in Information and Communication Technology, vol 519. Springer, Cham. | en_ZA |
| dc.identifier.issn | 1868-4238 (print) | |
| dc.identifier.issn | 1868-422X (online) | |
| dc.identifier.other | 10.1007/978-3-319-92007-8_6 | |
| dc.identifier.uri | http://hdl.handle.net/2263/66121 | |
| dc.language.iso | en | en_ZA |
| dc.publisher | Springer | en_ZA |
| dc.rights | © IFIP International Federation for Information Processing 2018. Published by Springer International Publishing AG 2018. All Rights Reserved. The original publication is available at : https://link.springer.com/bookseries/6102. | en_ZA |
| dc.subject | Spatial patterns | en_ZA |
| dc.subject | Diagrams | en_ZA |
| dc.subject | Ontology | en_ZA |
| dc.subject | Ontology reasoner | en_ZA |
| dc.subject | Scalable vector graphics (SVG) | en_ZA |
| dc.subject | Web ontology language (OWL) | en_ZA |
| dc.subject | Unified modelling language (UML) | en_ZA |
| dc.subject | UML class diagrams | en_ZA |
| dc.subject | Pattern recognition | en_ZA |
| dc.subject | Spatial arrangement | en_ZA |
| dc.subject | Instance classification | en_ZA |
| dc.subject | Domain concepts | en_ZA |
| dc.subject | Automated recognition | en_ZA |
| dc.subject | Graphic methods | en_ZA |
| dc.subject | Automation | en_ZA |
| dc.subject | Artificial intelligence (AI) | en_ZA |
| dc.title | Ontology-based spatial pattern recognition in diagrams | en_ZA |
| dc.type | Postprint Article | en_ZA |
