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Semantic data ingestion for intelligent, value-driven big data analytics
Debattista, Jeremy; Attard, Judie; Brennan, Rob
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.
Keyword(s): AI ensembles; Intelligent Analytics; Semantics; Data Governance
Publication Date:
2018
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Debattista, Jeremy, Attard, Judie ORCID: 0000-0001-7507-1864 <https://orcid.org/0000-0001-7507-1864> and Brennan, Rob ORCID: 0000-0001-6546-6408 <https://orcid.org/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.
Publisher(s): IEEE
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/22985/1/BigDataInnovationsAndApplications2018paper.pdf,
http://dx.doi.org/10.1109/Innovate-Data.2018.00008
First Indexed: 2019-02-16 06:13:36 Last Updated: 2019-02-16 06:13:36