RESOURCE-AWARE HIGH QUALITY CLUSTERING IN UBIQUITOUS DATA STREAMS

Ching-Ming Chao, Guan-Lin Chao

2011

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

  1. Aggarwal, C. C., Han, J., Wang, J., Yu, P. S., 2003. A Framework for Clustering Evolving Data Streams. In Proceedings of the 29th International Conference on Very Large Data Bases, Berlin, Germany, pp. 81-92.
  2. Aggarwal, C. C., Han, J., Wang, J., Yu, P. S., 2003. A Framework for Clustering Evolving Data Streams. In Proceedings of the 29th International Conference on Very Large Data Bases, Berlin, Germany, pp. 81-92.
  3. Babcock, B., Babu, S., Motwani, R., Widom, J., 2002. Models and Issues in Data Stream Systems. In Proceedings of the 21st ACM SIGMOD Symposium on Principles of Database Systems, Madison, Wisconsin, U.S.A., pp. 1-16.
  4. Babcock, B., Babu, S., Motwani, R., Widom, J., 2002. Models and Issues in Data Stream Systems. In Proceedings of the 21st ACM SIGMOD Symposium on Principles of Database Systems, Madison, Wisconsin, U.S.A., pp. 1-16.
  5. Dai, B. R., Huang, J. W., Yeh, M. Y., Chen, M. S., 2006. Adaptive Clustering for Multiple Evolving Streams. IEEE Transactions on Knowledge and Data Engineering, Vol. 18, No. 9, pp. 1166-1180.
  6. Dai, B. R., Huang, J. W., Yeh, M. Y., Chen, M. S., 2006. Adaptive Clustering for Multiple Evolving Streams. IEEE Transactions on Knowledge and Data Engineering, Vol. 18, No. 9, pp. 1166-1180.
  7. Gaber, M. M., Zaslavsky, A., Krishnaswamy, S., 2004. Towards an Adaptive Approach for Mining Data Streams in Resource Constrained Environment. In proceedings of the International Conference on Data Warehousing and Knowledge Discovery, Zaragoza, Spain, pp. 189-198.
  8. Gaber, M. M., Zaslavsky, A., Krishnaswamy, S., 2004. Towards an Adaptive Approach for Mining Data Streams in Resource Constrained Environment. In proceedings of the International Conference on Data Warehousing and Knowledge Discovery, Zaragoza, Spain, pp. 189-198.
  9. Gaber, M. M., Krishnaswamy, S., Zaslavsky, A., 2004. Ubiquitous Data Stream Mining. In Proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Sydney, Australia.
  10. Gaber, M. M., Krishnaswamy, S., Zaslavsky, A., 2004. Ubiquitous Data Stream Mining. In Proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Sydney, Australia.
  11. Gaber, M. M., Yu, P. S., 2006. A Framework for Resource-aware Knowledge Discovery in Data Streams: A Holistic Approach with Its Application to Clustering. In Proceedings of the 2006 ACM Symposium on Applied Computing, Dijon, France, pp. 649-656.
  12. Gaber, M. M., Yu, P. S., 2006. A Framework for Resource-aware Knowledge Discovery in Data Streams: A Holistic Approach with Its Application to Clustering. In Proceedings of the 2006 ACM Symposium on Applied Computing, Dijon, France, pp. 649-656.
  13. Golab, L., Ozsu, T. M., 2003. Issues in Data Stream Management ACM SIGMOD Record, Vol. 32, Issue 2, pp. 5-14.
  14. Golab, L., Ozsu, T. M., 2003. Issues in Data Stream Management ACM SIGMOD Record, Vol. 32, Issue 2, pp. 5-14.
  15. Kargupta, H., Park, B. H., Pittie, S., Liu, L., Kushraj, D., Sarkar, K., 2002. MobiMine: Monitoring the Stock Market from a PDA. ACM SIGKDD Explorations Newsletter, Vol. 3, No. 2, pp. 37-46.
  16. Kargupta, H., Park, B. H., Pittie, S., Liu, L., Kushraj, D., Sarkar, K., 2002. MobiMine: Monitoring the Stock Market from a PDA. ACM SIGKDD Explorations Newsletter, Vol. 3, No. 2, pp. 37-46.
  17. Kargupta, H., Bhargava, R., Liu, K., Powers, M., Blair, P., Bushra, S., Dull, J., Sarkar, K., Klein, M., Vasa, M., Handy, D., 2004. VEDAS: a Mobile and Distributed Data Stream Mining System for Real-Time Vehicle Monitoring. In Proceedings of the 4th SIAM International Conference on Data Mining, Florida, U.S.A., pp. 300-311.
  18. Kargupta, H., Bhargava, R., Liu, K., Powers, M., Blair, P., Bushra, S., Dull, J., Sarkar, K., Klein, M., Vasa, M., Handy, D., 2004. VEDAS: a Mobile and Distributed Data Stream Mining System for Real-Time Vehicle Monitoring. In Proceedings of the 4th SIAM International Conference on Data Mining, Florida, U.S.A., pp. 300-311.
  19. Shah, R., Krishnaswamy, S., Gaber, M. M., 2005. Resource-Aware Very Fast K-Means for Ubiquitous Data Stream Mining. In Proceedings of 2nd International Workshop on Knowledge Discovery in Data Streams, Porto, Portugal, pp. 40-50.
  20. Shah, R., Krishnaswamy, S., Gaber, M. M., 2005. Resource-Aware Very Fast K-Means for Ubiquitous Data Stream Mining. In Proceedings of 2nd International Workshop on Knowledge Discovery in Data Streams, Porto, Portugal, pp. 40-50.
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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 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 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


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