Abstract
This work investigates how to generate RDFS based knowledge graph from SBVR. Semantic web is developed the idea of Resource description Framework (RDF). Knowledge graph is collection of interconnected entities. We required RDF knowledge graph because we want to show the date, which represented in graph. RDF vocabulary is used to provide description of instances. RDF can be constructed by three components subject, object, and predicate in which subject and object are resources while predicate is the property which describe the relationship between these resources. In this paper we represented that how we Generate an RDFS based knowledge graph from SBVR Semantic of Business Vocabulary and Rules (SBVR) in a way that it is easy to machine process. We used SBVR Tool and described that with the help of that tool SBVR to RDF transformation is possible. In this method SBVR is our input, SBVR is a textual representation, we used SBVR rules and create triple (subject object predicate) and then generate RDF and RDFS.
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References
Ahmeti, A., Calvanese, D., Polleres, A.: Updating RDFS ABoxes and TBoxes in SPARQL. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8796, pp. 441–456. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11964-9_28
Bajwa, I.S., Lee, M.G., Bordbar, B.: SBVR business rules generation from natural language specification. In: AAAI Spring Symposium: AI for Business Agility, pp. 2–8, March 2011
Fürber, C., Hepp, M.: Towards a vocabulary for data quality management in semantic web architectures. In: Proceedings of the 1st International Workshop on Linked Web Data Management, pp. 1–8. ACM, March 2011
Aasman, J.: Event processing using an RDF database. In: AAAI Spring Symposium: Intelligent Event Processing, pp. 1–5 (2009)
Kerdjoudj, F., Curé, O.: RDF knowledge graph visualization from a knowledge extraction system. arXiv preprint arXiv:1510.00244 (2015)
Goasdoué, F., Manolescu, I., Roatiş, A.: Getting more RDF support from relational databases. In: Proceedings of the 21st International Conference on World Wide Web, pp. 515–516. ACM, April 2012
Khan, J.A., Kumar, S.: OWL, RDF, RDFS inference derivation using Jena semantic framework & pellet reasoner. In: 2014 International Conference on Advances in Engineering and Technology Research (ICAETR), pp. 1–8. IEEE, August 2014
Elbassuoni, S., Ramanath, M., Schenkel, R., Weikum, G.: Searching RDF graphs with SPARQL and keywords. IEEE Data Eng. Bull. 33(1), 16–24 (2010)
Bray, T., Paoli, J., Sperberg-McQueen, C.M., Maler, E., Yergeau, F.: Extensible markup language (XML). World Wide Web J. 2(4), 27–66 (1997)
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Akhtar, B., Mehmood, A., Mehmood, A., Noor, W. (2019). Generating RDFS Based Knowledge Graph from SBVR. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_53
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DOI: https://doi.org/10.1007/978-981-13-6052-7_53
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