Debattista, Jeremy, Attard, Judie ORCID: 0000-0001-7507-1864 and Brennan, Rob ORCID: 0000-0001-6546-6408 (2018) Semantic data ingestion for intelligent, value-driven big data analytics. In: 4th International Conference on Big Data Innovations and Applications (Innovate-Data), 6-8 Aug 2018, Barcelona, Spain.
Abstract
In this position paper we describe a conceptual
model for intelligent Big Data analytics based on both semantic
and machine learning AI techniques (called AI ensembles). These
processes are linked to business outcomes by explicitly modelling
data value and using semantic technologies as the underlying
mode for communication between the diverse processes and
organisations creating AI ensembles. Furthermore, we show
how data governance can direct and enhance these ensembles
by providing recommendations and insights that to ensure the
output generated produces the highest possible value for the
organisation.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | AI ensembles; Intelligent Analytics; Semantics; Data Governance |
Subjects: | UNSPECIFIED |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Institutes and Centres > ADAPT |
Published in: | 2018 4th International Conference on Big Data Innovations and Applications (Innovate-Data), Proceedings. . IEEE. |
Publisher: | IEEE |
Official URL: | http://dx.doi.org/10.1109/Innovate-Data.2018.00008 |
Copyright Information: | © 2018 The Authors |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Irish Research Council Government of Ireland Postdoctoral Fellowship award (GOIPD/2017/1204), the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 713567 (EDGE), SFI Research Centres Programme (Grant 13/RC/2106) and co-funded by the European Regional Development Fund |
ID Code: | 22985 |
Deposited On: | 15 Feb 2019 12:54 by Thomas Murtagh . Last Modified 15 Feb 2019 12:54 |
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