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Geometrical and topological approaches to big data

Autor
Snasel, V.; Nowaková, J.; Xhafa, F.; Barolli, L.
Tipus d'activitat
Article en revista
Revista
Future generation computer systems
Data de publicació
2016-06-29
DOI
https://doi.org/10.1016/j.future.2016.06.005 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/89691 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0167739X16301856 Obrir en finestra nova
Resum
Modern data science uses topological methods to find the structural features of data sets before further supervised or unsupervised analysis. Geometry and topology are very natural tools for analysing massive amounts of data since geometry can be regarded as the study of distance functions. Mathematical formalism, which has been developed for incorporating geometric and topological techniques, deals with point cloud data sets, i.e. finite sets of points. It then adapts tools from the various bra...
Citació
Snasel, V., Nowaková, J., Xhafa, F., Barolli, L. Geometrical and topological approaches to big data. "Future generation computer systems", 29 Juny 2016.
Paraules clau
Big data, Big data visualization, Dimensionality reduction, Industry 4.0, Persistent homology, Topological data analysis

Participants

  • Snasel, Vaclav  (autor)
  • Nowaková, Jana  (autor)
  • Xhafa Xhafa, Fatos  (autor)
  • Barolli, Leonard  (autor)