A Survey of Distributed Clustering Algorithms

Clustering is to divide a set of objects into multiple classes, and each class is made up of similar objects. Traditional centralized clustering algorithms cluster objects stored in a single site, but it cannot satisfy the clustering requirements when objects are distributed. Distributed clustering...

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Bibliographic Details
Published in2012 International Conference on Industrial Control and Electronics Engineering pp. 1142 - 1145
Main Authors Mo Hai, Shuyun Zhang, Lei Zhu, Yue Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2012
Subjects
Accuracy
Algorithm design and analysis
centralized clustering
Classification algorithms
clustering accuracy
Clustering algorithms
clustering time
Computers
distributed clustering
Distributed databases
Partitioning algorithms
Online AccessGet full text
ISBN1467314501
9781467314503
DOI10.1109/ICICEE.2012.303

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Summary:Clustering is to divide a set of objects into multiple classes, and each class is made up of similar objects. Traditional centralized clustering algorithms cluster objects stored in a single site, but it cannot satisfy the clustering requirements when objects are distributed. Distributed clustering algorithms can satisfy this need, which extracts a classification mode from distributed objects. This paper classifies and analyzes typical distributed clustering algorithms. Two data sets-Iris and Wine are used to compare several distributed clustering algorithms from two metrics: clustering accuracy and clustering time.
ISBN:1467314501
9781467314503
DOI:10.1109/ICICEE.2012.303