Indexing and Mining Streams
Summary: Tutorial on indexing and mining sensor streams: patterns, compression, forecasting, outlier detection. Unique in uniting fast similarity search, AR/ARIMA forecasting, and nonlinear fractal methods with intuition and practical case studies. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Christos Faloutsos (Carnegie Mellon University)
BibTeX Citation
@inproceedings{faloutsos_sigmod04,
title = {{Indexing and Mining Streams}},
author = {Faloutsos, Christos},
series = {{SIGMOD} '04},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1007568.1007728},
url = {https://dl.acm.org/doi/10.1145/1007568.1007728},
year = {2004}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2 | R-Trees: A Dynamic Index Structure For Spatial Searching | 1984 | SIGMOD | 0.0019923528 |
| 56 | M-tree: An Efficient Access Method for Similarity Search in Metric Spaces | 1997 | VLDB | 0.00040363819 |
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