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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 263-266On Density-Based Clustering Algorithms over...

On Density-Based Clustering Algorithms over Evolving Data Streams: A Summarization Paradigm

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Abstract:

Clustering is one of the prominent classes in the mining data streams. Among various clustering algorithms that have been developed, density-based method has the ability to discover arbitrary shape clusters, and to detect the outliers. Recently, various algorithms adopted density-based methods for clustering data streams. In this paper, we look into three remarkable algorithms in two groups of micro-clustering and grid-based including DenStream, D-Stream, and MR-Stream. We compare the algorithms based on evaluating algorithm performance and clustering quality metrics.

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Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

2234-2237

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.2234

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Cite this paper

Online since:

December 2012

Authors:

Amineh Amini, Teh Ying Wah

Keywords:

Density-Based Algorithms, Denstream, D-Stream, Evolving Data Streams, MR-Stream

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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