Streaming-data algorithms for high-quality clustering. O'Callaghan, L., Mishra, N., Meyerson, A., Guha, S., & Motwani, R. In Proceedings 18th International Conference on Data Engineering, pages 685–694, February, 2002. ISSN: 1063-6382doi abstract bibtex Streaming data analysis has recently attracted attention in numerous applications including telephone records, Web documents and click streams. For such analysis, single-pass algorithms that consume a small amount of memory are critical. We describe such a streaming algorithm that effectively clusters large data streams. We also provide empirical evidence of the algorithm's performance on synthetic and real data streams.
@inproceedings{ocallaghan_streaming-data_2002,
title = {Streaming-data algorithms for high-quality clustering},
doi = {10.1109/ICDE.2002.994785},
abstract = {Streaming data analysis has recently attracted attention in numerous applications including telephone records, Web documents and click streams. For such analysis, single-pass algorithms that consume a small amount of memory are critical. We describe such a streaming algorithm that effectively clusters large data streams. We also provide empirical evidence of the algorithm's performance on synthetic and real data streams.},
booktitle = {Proceedings 18th {International} {Conference} on {Data} {Engineering}},
author = {O'Callaghan, L. and Mishra, N. and Meyerson, A. and Guha, S. and Motwani, R.},
month = feb,
year = {2002},
note = {ISSN: 1063-6382},
keywords = {Algorithm design and analysis, Clustering algorithms, Computer science, Data analysis, Data engineering, Lab-on-a-chip, Laboratories, Partitioning algorithms, Telecommunications, Telephony},
pages = {685--694},
}
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