Double Deep Autoencoder for Heterogeneous Distributed Clustering

Double Deep Autoencoder for Heterogeneous Distributed Clustering

Given the issues relating to big data and privacy-preserving challenges, distributed data mining (DDM) has received much attention recently. Here, we focus on the clustering problem of distributed environments. Several distributed clustering algorithms have been proposed to solve this problem, howev...

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Bibliographic Details
Main Authors: Chin-Yi Chen, Jih-Jeng Huang
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Information
Subjects:
distributed data mining (DDM)
clustering
big data
heterogeneous databases
deep autoencoder
Online Access:https://www.mdpi.com/2078-2489/10/4/144

Internet

https://www.mdpi.com/2078-2489/10/4/144

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