DeltaDens - incremental algorithm for on-line density-based clustering

Radosław Z. Ziembiński

doi:10.1007/978-3-642-32518-2_16

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Title

DeltaDens - incremental algorithm for on-line density-based clustering

Authors

Radosław Z. Ziembiński (WI) ^{[ 1 ][ P ]}

^{[ 1 ]} Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | ^{[ P ]} employee

Year of publication

2013

Chapter type

paper

Publication language

english

Keywords

EN

Density–based Clustering
On–line Clustering
Data Streams

Abstract

EN Cluster analysis of data delivered in a stream exhibits some unique properties. They make the clustering more difficult than it happens for the static set of data. This paper introduces a new DeltaDens clustering algorithm that can be used for this purpose. It is a density–based algorithm, capable of finding an unbound number of irregular clusters. The algorithm’s per–iteration processing time linearly depends on the size of its internal buffer. The paper describes the algorithm and delivers some experimental results explaining its performance and accuracy.

Pages (from - to)

163 - 172

DOI

10.1007/978-3-642-32518-2_16

URL

https://link.springer.com/chapter/10.1007/978-3-642-32518-2_16

Book

New Trends in Databases and Information Systems

Presented on

16th East-European Conference on Advances in Databases and Information Systems, ADBIS 2012, 17-21.09.2012, Poznan, Poland

Publication indexed in

WoS (15)

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