Occam’s Razor for <i>Big Data</i>? On Detecting Quality in Large Unstructured Datasets

Occam’s Razor for <i>Big Data</i>? On Detecting Quality in Large Unstructured Datasets

Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic c...

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Bibliographic Details
Main Authors: Birgitta Dresp-Langley, Ole Kristian Ekseth, Jan Fesl, Seiichi Gohshi, Marc Kurz, Hans-Werner Sehring
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Applied Sciences
Subjects:
<i>big data</i>
non-dimensionality
applied data science
paradigm shift
artificial intelligence
principle of parsimony (<i>Occam’s razor</i>)
Online Access:https://www.mdpi.com/2076-3417/9/15/3065

Internet

https://www.mdpi.com/2076-3417/9/15/3065

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