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Original version
Gottschalk, S.; Tempelmeier, N.; Kniesel, G.; Iosifidis, V.; Fetahu, B. et al.: Simple-ML: Towards a Framework for Semantic Data Analytics Workflows. In: Acosta, M.; Cudré-Mauroux, P.; Maleshkova, M.; Pellegrini, T.; Sack, H.; Sure-Vetter, Y. (Eds.): Semantic Systems. The Power of AI and Knowledge Graphs. Heidelberg : Springer Verlag, 2019 (Lecture Notes in Computer Science ; 11702), S. 359-366. DOI: https://doi.org/10.1007/978-3-030-33220-4_26
Repository version
To cite the version in the repository, please use this identifier:
https://doi.org/10.15488/10234
Files in this item
| Abstract: | |
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In this paper we present the Simple-ML framework that we develop to support efficient configuration, robustness and reusability of data analytics workflows through the adoption of semantic technologies. We present semantic data models that lay the foundation for the framework development and discuss the data analytics workflows based on these models. Furthermore, we present an example instantiation of the Simple-ML data models for a real-world use case in the mobility domain. © 2019, The Author(s).
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| License of this version: | CC BY 4.0 Unported - https://creativecommons.org/licenses/by/4.0/ |
| Publication type: | BookPart |
| Publishing status: | publishedVersion |
| Publication date: | 2019 |
| Keywords english: | Reusability, Semantics, Framework development, Real-world, Semantic data model, Semantic technologies, Work-flows, Data Analytics |
| DDC: | 004 | Informatik |
| Controlled keywords(GND): | Konferenzschrift |
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