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Open AccessArticle

Clustering Neutrosophic Data Sets and Neutrosophic Valued Metric Spaces

1
Department of Mathematics, Faculty of Science, İstanbul University, İstanbul 34134, Turkey
2
Department of Mathematics, Faculty of Science and Arts, Bitlis Eren University, Bitlis 13000, Turkey
3
Department of Mathematics, University of New Mexico, Gallup, NM 87301, USA
*
Author to whom correspondence should be addressed.
Symmetry 2018, 10(10), 430; https://doi.org/10.3390/sym10100430
Received: 5 August 2018 / Revised: 11 September 2018 / Accepted: 21 September 2018 / Published: 24 September 2018
In this paper, we define the neutrosophic valued (and generalized or G) metric spaces for the first time. Besides, we newly determine a mathematical model for clustering the neutrosophic big data sets using G-metric. Furthermore, relative weighted neutrosophic-valued distance and weighted cohesion measure, is defined for neutrosophic big data set. We offer a very practical method for data analysis of neutrosophic big data although neutrosophic data type (neutrosophic big data) are in massive and detailed form when compared with other data types. View Full-Text
Keywords: G-metric; neutrosophic G-metric; neutrosophic sets; clustering; neutrosophic big data; neutrosophic logic G-metric; neutrosophic G-metric; neutrosophic sets; clustering; neutrosophic big data; neutrosophic logic
MDPI and ACS Style

Taş, F.; Topal, S.; Smarandache, F. Clustering Neutrosophic Data Sets and Neutrosophic Valued Metric Spaces. Symmetry 2018, 10, 430. https://doi.org/10.3390/sym10100430

AMA Style

Taş F, Topal S, Smarandache F. Clustering Neutrosophic Data Sets and Neutrosophic Valued Metric Spaces. Symmetry. 2018; 10(10):430. https://doi.org/10.3390/sym10100430

Chicago/Turabian Style

Taş, Ferhat; Topal, Selçuk; Smarandache, Florentin. 2018. "Clustering Neutrosophic Data Sets and Neutrosophic Valued Metric Spaces" Symmetry 10, no. 10: 430. https://doi.org/10.3390/sym10100430

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