Efficient distributed clustering using boundary information

Neurocomputing, pp. 2355-2366, 2018.

Cited by: 13|Bibtex|Views17|DOI:https://doi.org/10.1016/j.neucom.2017.11.014
EI WOS SCOPUS
Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

In the era of big data, it is increasingly common that large amount of data is generated across multiple distributed sites and cannot be gathered into a centralized site for further analysis, which invalidates the assumption of traditional clustering techniques based on centralized models. The major challenge is that these distributed dat...More

Code:

Data:

Your rating :
0

 

Tags
Comments