Title :
A Comparative Analysis of Distributed Clustering Algorithms: A Survey
Author :
Singh, D. ; Gosain, Anjana
Author_Institution :
USICT GGSIP Univ., New Delhi, India
Abstract :
Cluster analysis (or clustering) is one of the most common techniques used for data mining. It is a process in which a given set of objects is assigned into groups, where these groups are known as clusters. Objects belonging to a single cluster are similar to other objects in that cluster but different from the objects belonging to other clusters. The task of clustering becomes difficult and complex in case the data is distributed across multiple sites. Distributed clustering comes as a rescue to the problems of traditional clustering when applied to distributed databases. Many researchers have proposed clustering algorithms which work efficiently in the distributed environment. In this research paper we have provided the comparative analysis of some of these distributed clustering algorithms based on various parameters.
Keywords :
data mining; distributed databases; pattern clustering; data mining; distributed clustering algorithm; distributed databases; Algorithm design and analysis; Clustering algorithms; Data models; Data privacy; Distributed databases; Partitioning algorithms; centralized clustering; clustering; distributed clustering; heterogeneous datasets; homogenous datasets;
Conference_Titel :
Computational and Business Intelligence (ISCBI), 2013 International Symposium on
Conference_Location :
New Delhi
Print_ISBN :
978-0-7695-5066-4
DOI :
10.1109/ISCBI.2013.40