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