RESOURCE-AWARE HIGH QUALITY CLUSTERING IN UBIQUITOUS DATA STREAMS

Ching-Ming Chao, Guan-Lin Chao

Abstract

Data stream mining has attracted much research attention from the data mining community. With the advance of wireless networks and mobile devices, the concept of ubiquitous data mining has been proposed. However, mobile devices are resource-constrained, which makes data stream mining a greater challenge. In this paper, we propose the RA-HCluster algorithm that can be used in mobile devices for clustering stream data. It adapts algorithm settings and compresses stream data based on currently available resources, so that mobile devices can continue with clustering at acceptable accuracy even under low memory resources. Experimental results show that not only is RA-HCluster more accurate than RA-VFKM, it is able to maintain a low and stable memory usage.

References

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Paper Citation


in Harvard Style

Chao C. and Chao G. (2011). RESOURCE-AWARE HIGH QUALITY CLUSTERING IN UBIQUITOUS DATA STREAMS . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8425-53-9, pages 64-73. DOI: 10.5220/0003467700640073


in Bibtex Style

@conference{iceis11,
author={Ching-Ming Chao and Guan-Lin Chao},
title={RESOURCE-AWARE HIGH QUALITY CLUSTERING IN UBIQUITOUS DATA STREAMS},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2011},
pages={64-73},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003467700640073},
isbn={978-989-8425-53-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - RESOURCE-AWARE HIGH QUALITY CLUSTERING IN UBIQUITOUS DATA STREAMS
SN - 978-989-8425-53-9
AU - Chao C.
AU - Chao G.
PY - 2011
SP - 64
EP - 73
DO - 10.5220/0003467700640073