2018•International Journal of Computers and ApplicationsRequires access

Affinity propagation clustering algorithm based on large-scale data-set

Limin Wang, Kaiyue Zheng, Tao Xing, Xuming Han

Open publisher page 16 citations

Abstract

Affinity Propagation (AP) algorithm is not effective in processing large-scale data-sets, so the paper purposed an affinity propagation clustering algorithm based on large scale data-set, called LD-AP. First, we use the idea of grid clustering to divide large data-sets into small datasets and running AP in them to ensure the center of clustering. Then, we introduced the structure similarity matrix to calculate the distance of the cluster center. At last, we used Density peak Clustering Algorithm (DP) algorithm to cluster the cluster again. The experimental results show that the improved algorithm is better than the original algorithm in the clustering effect and computation speed.

About this research paper

What this paper is about

Affinity Propagation (AP) algorithm is not effective in processing large-scale data-sets, so the paper purposed an affinity propagation clustering algorithm based on large scale data-set, called LD-AP. First, we use the idea of grid clustering to divide large data-sets into small datasets and running AP in them to ensure the center of clustering. Then, we introduced the structure similarity matrix to calculate the distance of the cluster center. At last, we used Density peak Clustering Algorithm (DP) algorithm to cluster the cluster again. The experimental results show that the improved algorithm is better than the original algorithm in the clustering effect and computation speed.

Why it matters

OpenAlex reports 16 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Affinity Propagation (AP) algorithm is not effective in processing large-scale data-sets, so the paper purposed an affinity propagation clustering algorithm based on large scale data-set, called LD-AP. First, we use the idea of grid clustering to divide large data-sets into small datasets and running AP in them to ensure the center of clustering. Then, we introduced the structure similarity matrix to calculate the distance of the cluster center. At last, we used Density peak Clustering Algorithm (DP) algorithm to cluster the cluster again. The experimental results show that the improved algorithm is better than the original algorithm in the clustering effect and computation speed.

Key concepts: Affinity propagation, Cluster analysis, Computer science, CURE data clustering algorithm, Canopy clustering algorithm, Correlation clustering, Data stream clustering, Single-linkage clustering

Related papers

Back to paper searchBrowse research topicsOriginal source
Affinity propagation clustering algorithm based on large-scale data-set — Research Paper | ScholarLens