The DOI matches its Crossref record.
An Approximate L p-Difference Algorithm for Massive Data Streams: Extended Abstract
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Citations
Cited by
An improved data stream summary: the count-min sketch and its applications
Cormode, G., & Muthukrishnan, S. (2005) · Journal of Algorithms · doi:10.1016/j.jalgor.2003.12.001 · Cited by 1,743
Gossip-based computation of aggregate information
Kempe, D., Dobra, A., & Gehrke, J. (2004) · 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings. · doi:10.1109/sfcs.2003.1238221 · Cited by 1,480
Maintaining Stream Statistics over Sliding Windows
Datar, M., Gionis, A., Indyk, P., & Motwani, R. (2002) · SIAM Journal on Computing · doi:10.1137/s0097539701398363 · Cited by 835
Algorithmic applications of low-distortion geometric embeddings
Indyk, P. (2001) · Proceedings 42nd IEEE Symposium on Foundations of Computer Science · doi:10.1109/sfcs.2001.959878 · Cited by 253
Metadata
- Authors
- Fong, J. H., & Strauss, M. J.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2000
- Pages
- 193-204
- ISSN
- 0302-9743 (ISSN-L)
- OpenAlex
- W2156943642
- Cited by
- 163
- References
- 0
- FWCI
- 14.39
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Approximate L p-Difference Algorithm for Massive Data Streams: Extended Abstract. https://app.cochat.ai/papers/10.1007/3-540-46541-3_16
- The paper
- Fong, J. H., & Strauss, M. J. (2000). An Approximate L p-Difference Algorithm for Massive Data Streams: Extended Abstract. Lecture Notes in Computer Science. https://doi.org/10.1007/3-540-46541-3_16
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
