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Incremental DBSCAN Algorithm in Distributed Data Mining

Author(s):

Patel Chaitalij , Vedica Institute of Technology Bhopal; Akhilesh Basiya, Vedica Institute of Technology Bhopal

Keywords:

DBSAN, Time Complexity, Distributed Environment, Java, Cluster

Abstract

A Density-based spatial clustering o application with noise (DBSCAN) is a data clustering algorithm is density based algorithm to find clusters of arbitrary shapes. This algorithm is used to find the clusters in discretionary images or shapes, size and also filter out noise. There are lots of algorithms are invented to improve DBSCAN algorithm in many different ways like time complexity, efficiency, performance. In this research such algorithm will be develop that can work in the distributed environment using the Eclipse Helios with java language that will reduce time o the existing algorithm and dataset are different and also different site, it will work with the single node and check or find the proper or suitable result in the distributed environment.

Other Details

Paper ID: IJSRDV6I30673
Published in: Volume : 6, Issue : 3
Publication Date: 01/06/2018
Page(s): 1441-1444

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