Distributed clustering using multi-tier hierarchical overlay super-peer peer-to-peer network architecture for efficient customer segmentation

作者:

Highlights:

• We propose a multi-layer hierarchical super-peer P2P network architecture to actuate the distributed clustering problem Vs. centralized Clustering.

• The proposed distributed clustering algorithm has achieved an improved in the computational speed without compromising the clustering quality or accuracy.

• The proposed architecture can be used in various types of data sets with different sizes and configuration in addition to the customer dataset used in the paper.

• The proposed architecture has been applied to various unsupervised machine learning algorithm showing its effectiveness.

摘要

•We propose a multi-layer hierarchical super-peer P2P network architecture to actuate the distributed clustering problem Vs. centralized Clustering.•The proposed distributed clustering algorithm has achieved an improved in the computational speed without compromising the clustering quality or accuracy.•The proposed architecture can be used in various types of data sets with different sizes and configuration in addition to the customer dataset used in the paper.•The proposed architecture has been applied to various unsupervised machine learning algorithm showing its effectiveness.

论文关键词:E-Commerce,Customer Segmentation,P2P Networks,Speed-up

论文评审过程:Received 4 September 2020, Revised 8 February 2021, Accepted 3 March 2021, Available online 12 March 2021, Version of Record 1 April 2021.

论文官网地址:https://doi.org/10.1016/j.elerap.2021.101040